기말고사_해보기.ipynb

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          "text": [
            "Writing C:\\myPyCode\\my_first_module.py\n"
          ]
        }
      ],
      "source": [
        "%%writefile C:\\myPyCode\\my_first_module.py\n",
        "def my_function():\n",
        "  print(\"This is my first module.\")"
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      "cell_type": "code",
      "source": [
        "import my_first_module\n",
        "my_first_module.my_function()"
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            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
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            "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'my_first_module'",
            "",
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0;32m\nNOTE: If your import is failing due to a missing package, you can\nmanually install dependencies using either !pip or !apt.\n\nTo view examples of installing some common dependencies, click the\n\"Open Examples\" button below.\n\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n"
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              "[4, 1]"
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          "metadata": {},
          "execution_count": 4
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    },
    {
      "cell_type": "code",
      "source": [
        "import datetime\n",
        "print(datetime.date.today())"
      ],
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        "id": "hNLtUK1lx0SL",
        "outputId": "ba6f22f5-01bd-4a27-965b-be31e703cbcf"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2024-06-12\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import datetime\n",
        "now=datetime.datetime.now()\n",
        "print(now)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1HGdhXnK09OH",
        "outputId": "69d19d5a-910a-4ce4-ad41-951c7a05cfd1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2024-06-12 00:27:19.801378\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from datetime import date,time,datetime\n",
        "print(date(2019,7,1))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LR03T70714su",
        "outputId": "2feeb43c-a3d2-4aa6-c6f4-35f83a6359a3"
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      "execution_count": null,
      "outputs": [
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          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2019-07-01\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(date.today())"
      ],
      "metadata": {
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        },
        "id": "-SFUQYNk3LCc",
        "outputId": "b4a457cb-aa10-4aba-98b1-d5bd860a842a"
      },
      "execution_count": null,
      "outputs": [
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          "name": "stdout",
          "text": [
            "2024-06-12\n"
          ]
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(time(15,30,45))"
      ],
      "metadata": {
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        "id": "uL1vHr-J3NkW",
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "15:30:45\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import calendar\n",
        "print(calendar.month(2020,9))\n",
        "calendar.setfirstweekday(6)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "POXQeIsE3SaC",
        "outputId": "de021f43-abf2-4d99-badf-3251270ab7c2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   September 2020\n",
            "Mo Tu We Th Fr Sa Su\n",
            "    1  2  3  4  5  6\n",
            " 7  8  9 10 11 12 13\n",
            "14 15 16 17 18 19 20\n",
            "21 22 23 24 25 26 27\n",
            "28 29 30\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(calendar.month(2020,9))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vCFj9S_J7SZY",
        "outputId": "25208bdf-007a-479a-b90d-16956c38ad97"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   September 2020\n",
            "Su Mo Tu We Th Fr Sa\n",
            "       1  2  3  4  5\n",
            " 6  7  8  9 10 11 12\n",
            "13 14 15 16 17 18 19\n",
            "20 21 22 23 24 25 26\n",
            "27 28 29 30\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np"
      ],
      "metadata": {
        "id": "qOT-k_TK8qNE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data1=[0,1,2,3,4,5]\n",
        "a1=np.array(data1)\n",
        "a1"
      ],
      "metadata": {
        "id": "zoPi8qjq8sEe",
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          "base_uri": "https://localhost:8080/"
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 1, 2, 3, 4, 5])"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.array([0.5,2,0.01,8])"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2pcklNhM9XYe",
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      "execution_count": null,
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.5 , 2.  , 0.01, 8.  ])"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#다차원 배열\n",
        "np.array([[1,2,3],[4,5,6],[7,8,9]])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "36T6R7-i9vVn",
        "outputId": "c1d9ae4f-5f39-45cf-dfdd-1aa33c639a5d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[1, 2, 3],\n",
              "       [4, 5, 6],\n",
              "       [7, 8, 9]])"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "stra1=np.array([1,2,3])\n",
        "numa1=stra1.astype(float)\n",
        "numa1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_4sgCSMy94vz",
        "outputId": "e5ca2803-95c3-4d4c-8a63-9110b557b798"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1., 2., 3.])"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "s1=pd.Series([1,2,3,4,5])\n",
        "s1"
      ],
      "metadata": {
        "id": "sER5gVaBDptm",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6c36afbc-35a8-48fb-f33d-a48e60b1f591"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    1\n",
              "1    2\n",
              "2    3\n",
              "3    4\n",
              "4    5\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "s1.index"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c951Pwl9QUNw",
        "outputId": "03dcb9cc-1ebf-4bff-e191-77cd0d742be4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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            "text/plain": [
              "RangeIndex(start=0, stop=5, step=1)"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "s1.values"
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        "id": "V4hJLX0AQbQH",
        "outputId": "3ffdcabc-84e8-41c7-8007-94a6f09cbd41"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1, 2, 3, 4, 5])"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "s5=pd.Series({'국어':100,'수학':95,'영어':85})\n",
        "s5"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ugm_oTu5QguX",
        "outputId": "b5894c05-a7d4-453d-dbee-ebbda17335b4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "국어    100\n",
              "수학     95\n",
              "영어     85\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "pd.DataFrame([[1,2,3],[4,5,6],[7,8,9]])"
      ],
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        {
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            "text/plain": [
              "   0  1  2\n",
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              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
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              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
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              "\n",
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              "  }\n",
              "\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
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              "  }\n",
              "\n",
              "  @keyframes spin {\n",
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              "    40% {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "    60% {\n",
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              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "    90% {\n",
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              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-d4edd9c3-ad99-4176-b353-681e7fc6f0cc button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
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            }
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "data=np.array([[1,2,3],[4,5,6],[7,8,9],[10,11,12]])\n",
        "index_date=pd.date_range('2019-09-01',periods=4)\n",
        "columns_list=['A','B','C']\n",
        "pd.DataFrame(data,index=index_date,columns=columns_list)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "aNkqeSCZVIdY",
        "outputId": "9e174c08-f9a4-410e-df57-40e674a99cae"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             A   B   C\n",
              "2019-09-01   1   2   3\n",
              "2019-09-02   4   5   6\n",
              "2019-09-03   7   8   9\n",
              "2019-09-04  10  11  12"
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-09-04</th>\n",
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              "        document.querySelector('#df-54a595f4-34fd-4507-9c7e-05c8673fd357 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
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              "        const element = document.querySelector('#df-54a595f4-34fd-4507-9c7e-05c8673fd357');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "    }\n",
              "  }\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
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              "        document.querySelector('#df-ba28e184-c4f7-45d8-b316-84364a19f59d button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
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              "</div>\n",
              "\n",
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          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "table_data={'연도':[2015,2016,2016,2017,2017],'지사':['한국','한국','미국','한국','미국'],'고객수':[200,250,450,300,500]}\n",
        "table_data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zZPZKQy5XBqU",
        "outputId": "97c30c7a-c2c4-45b3-d3a7-f3be0fbfffee"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'연도': [2015, 2016, 2016, 2017, 2017],\n",
              " '지사': ['한국', '한국', '미국', '한국', '미국'],\n",
              " '고객수': [200, 250, 450, 300, 500]}"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.DataFrame(table_data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "auhj9bI1X8Cj",
        "outputId": "3fac765e-60da-45ff-8572-d36f7dd9cbdf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     연도  지사  고객수\n",
              "0  2015  한국  200\n",
              "1  2016  한국  250\n",
              "2  2016  미국  450\n",
              "3  2017  한국  300\n",
              "4  2017  미국  500"
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>연도</th>\n",
              "      <th>지사</th>\n",
              "      <th>고객수</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2015</td>\n",
              "      <td>한국</td>\n",
              "      <td>200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2016</td>\n",
              "      <td>한국</td>\n",
              "      <td>250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2016</td>\n",
              "      <td>미국</td>\n",
              "      <td>450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2017</td>\n",
              "      <td>한국</td>\n",
              "      <td>300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2017</td>\n",
              "      <td>미국</td>\n",
              "      <td>500</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-89a1e6ca-e752-4000-8d00-921f7648ec31')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-89a1e6ca-e752-4000-8d00-921f7648ec31 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-89a1e6ca-e752-4000-8d00-921f7648ec31');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-3e4f1574-4204-4142-bd1e-8aaacc83ea57\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-3e4f1574-4204-4142-bd1e-8aaacc83ea57')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-3e4f1574-4204-4142-bd1e-8aaacc83ea57 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"pd\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"\\uc5f0\\ub3c4\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 2015,\n        \"max\": 2017,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          2015,\n          2016,\n          2017\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uc9c0\\uc0ac\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"\\ubbf8\\uad6d\",\n          \"\\ud55c\\uad6d\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uace0\\uac1d\\uc218\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 129,\n        \"min\": 200,\n        \"max\": 500,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          250,\n          500\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df=pd.DataFrame(table_data,columns=['연도','지사','고객수'])\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "eWRb5vG1YB8R",
        "outputId": "f08f5f75-175c-42aa-a236-25bf4e933145"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     연도  지사  고객수\n",
              "0  2015  한국  200\n",
              "1  2016  한국  250\n",
              "2  2016  미국  450\n",
              "3  2017  한국  300\n",
              "4  2017  미국  500"
            ],
            "text/html": [
              "\n",
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              "      <td>2017</td>\n",
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              "\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
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              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-a4ecba9e-7d4e-451a-ae95-486550f7502d button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-a4ecba9e-7d4e-451a-ae95-486550f7502d');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
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              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4bb6f743-9403-43a2-b307-ea4ab9cffaee')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "</svg>\n",
              "  </button>\n",
              "\n",
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              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
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              "\n",
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              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
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              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-4bb6f743-9403-43a2-b307-ea4ab9cffaee button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_af34a968-530a-49c4-b17c-c2f60a175e84\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_af34a968-530a-49c4-b17c-c2f60a175e84 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"\\uc5f0\\ub3c4\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 2015,\n        \"max\": 2017,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          2015,\n          2016,\n          2017\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uc9c0\\uc0ac\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"\\ubbf8\\uad6d\",\n          \"\\ud55c\\uad6d\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uace0\\uac1d\\uc218\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 129,\n        \"min\": 200,\n        \"max\": 500,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          250,\n          500\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "df1=pd.DataFrame({'Class1':[95,92,98,100],'Class2':[91,93,97,99]})\n",
        "df1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "bZ7m2nWXYVsh",
        "outputId": "b9b9c826-7eb6-4f45-f8ec-7e4341a0274f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Class1  Class2\n",
              "0      95      91\n",
              "1      92      93\n",
              "2      98      97\n",
              "3     100      99"
            ],
            "text/html": [
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              "      <th>Class1</th>\n",
              "      <th>Class2</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>95</td>\n",
              "      <td>91</td>\n",
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              "      <th>1</th>\n",
              "      <td>92</td>\n",
              "      <td>93</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>98</td>\n",
              "      <td>97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>100</td>\n",
              "      <td>99</td>\n",
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              "  </tbody>\n",
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              "    <div class=\"colab-df-buttons\">\n",
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              "\n",
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              "      width: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-b06f934b-b269-4878-801e-46fd8027a0f8 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-b06f934b-b269-4878-801e-46fd8027a0f8');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "  </div>\n",
              "\n",
              "\n",
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              "            title=\"Suggest charts\"\n",
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              "\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-51fa4df6-b497-47fd-bfe4-8163fa07803e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_c4221b02-705f-489d-b055-8c49f81c338a\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df1')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_c4221b02-705f-489d-b055-8c49f81c338a button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df1');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df1",
              "summary": "{\n  \"name\": \"df1\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"Class1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3,\n        \"min\": 92,\n        \"max\": 100,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          92,\n          100,\n          95\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Class2\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3,\n        \"min\": 91,\n        \"max\": 99,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          93,\n          99,\n          91\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2=pd.DataFrame({'Class1':[87,89],'Class2':[85,90]})\n",
        "df2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 125
        },
        "id": "TIblfCy8hjpg",
        "outputId": "06ee4bab-8e82-4d41-fa38-78b7d2fa9f05"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Class1  Class2\n",
              "0      87      85\n",
              "1      89      90"
            ],
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              "\n",
              "      .colab-df-generate:hover {\n",
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              "\n",
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              "\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df2",
              "summary": "{\n  \"name\": \"df2\",\n  \"rows\": 2,\n  \"fields\": [\n    {\n      \"column\": \"Class1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 87,\n        \"max\": 89,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          89,\n          87\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Class2\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3,\n        \"min\": 85,\n        \"max\": 90,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          90,\n          85\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df1.append(df2,ignore_index=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 273
        },
        "id": "qSht1ldWhwWS",
        "outputId": "8deadf5b-0836-48a4-a75d-99b484d312cc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "AttributeError",
          "evalue": "'DataFrame' object has no attribute 'append'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-21-f66c09b25164>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mignore_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m   5987\u001b[0m         ):\n\u001b[1;32m   5988\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5989\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5990\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5991\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: 'DataFrame' object has no attribute 'append'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df4=pd.DataFrame({'Class':[93,91,95,98]})\n",
        "df4"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "84RSRqCJhyTU",
        "outputId": "01bfbc4f-bf98-41db-fd0a-b830196cbf46"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Class\n",
              "0     93\n",
              "1     91\n",
              "2     95\n",
              "3     98"
            ],
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              "    <div class=\"colab-df-buttons\">\n",
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              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-0f9be92e-5735-4ba0-a5b5-7be8cf4a30b6 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-0f9be92e-5735-4ba0-a5b5-7be8cf4a30b6');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-33840a33-26bd-4f50-87f3-e61b7630291c\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-33840a33-26bd-4f50-87f3-e61b7630291c')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-33840a33-26bd-4f50-87f3-e61b7630291c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_1087b72e-039a-4758-b29f-ce9aeb0316a8\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df4')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_1087b72e-039a-4758-b29f-ce9aeb0316a8 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df4');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df4",
              "summary": "{\n  \"name\": \"df4\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"Class\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 91,\n        \"max\": 98,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          91,\n          98,\n          93\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df1.join(df4)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "Ugy8JTjYlTo8",
        "outputId": "3c8d5fe2-344a-4d80-b33e-7cddda8c654d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Class1  Class2  Class\n",
              "0      95      91     93\n",
              "1      92      93     91\n",
              "2      98      97     95\n",
              "3     100      99     98"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f8efefb7-8d28-4566-83db-e6f26a847e76\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Class1</th>\n",
              "      <th>Class2</th>\n",
              "      <th>Class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>95</td>\n",
              "      <td>91</td>\n",
              "      <td>93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>92</td>\n",
              "      <td>93</td>\n",
              "      <td>91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>98</td>\n",
              "      <td>97</td>\n",
              "      <td>95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>100</td>\n",
              "      <td>99</td>\n",
              "      <td>98</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f8efefb7-8d28-4566-83db-e6f26a847e76')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-f8efefb7-8d28-4566-83db-e6f26a847e76 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f8efefb7-8d28-4566-83db-e6f26a847e76');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-88d5fd43-932e-4cde-bae1-156fef4b751f\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-88d5fd43-932e-4cde-bae1-156fef4b751f')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-88d5fd43-932e-4cde-bae1-156fef4b751f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df1\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"Class1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3,\n        \"min\": 92,\n        \"max\": 100,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          92,\n          100,\n          95\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Class2\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3,\n        \"min\": 91,\n        \"max\": 99,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          93,\n          99,\n          91\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Class\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 91,\n        \"max\": 98,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          91,\n          98,\n          93\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "index_label=['a','b','c','d']\n",
        "df1a=pd.DataFrame({'Class1':[95,92,98,100],'Class2':[91,93,97,99]},index=index_label)\n",
        "df4a=pd.DataFrame({'Class3':[93,91,95,98]},index=index_label)\n",
        "df1a.join(df4)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "vF7WWN4AlV18",
        "outputId": "fc9f32e6-ec30-471c-e7a3-464ea16f725e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Class1  Class2  Class\n",
              "a      95      91    NaN\n",
              "b      92      93    NaN\n",
              "c      98      97    NaN\n",
              "d     100      99    NaN"
            ],
            "text/html": [
              "\n",
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              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>b</th>\n",
              "      <td>92</td>\n",
              "      <td>93</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>c</th>\n",
              "      <td>98</td>\n",
              "      <td>97</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>d</th>\n",
              "      <td>100</td>\n",
              "      <td>99</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-ff0f6e97-7383-4185-8347-d060fbcc9c8e button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-ff0f6e97-7383-4185-8347-d060fbcc9c8e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-21922791-3d8c-4748-8950-52d4ed5a9074\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-21922791-3d8c-4748-8950-52d4ed5a9074')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-21922791-3d8c-4748-8950-52d4ed5a9074 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df1a\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"Class1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3,\n        \"min\": 92,\n        \"max\": 100,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          92,\n          100,\n          95\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Class2\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3,\n        \"min\": 91,\n        \"max\": 99,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          93,\n          99,\n          91\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Class\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": null,\n        \"max\": null,\n        \"num_unique_values\": 0,\n        \"samples\": [],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_a_b=pd.DataFrame({'판매월':['1월','2월','3월','4월'],'제품a':[100,150,200,130],'제품b':[90,110,140,170]})\n",
        "df_a_b"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "DvD2wJ7YmYAy",
        "outputId": "b45f2de0-b011-4398-9dd5-d494b6d1fda0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  판매월  제품a  제품b\n",
              "0  1월  100   90\n",
              "1  2월  150  110\n",
              "2  3월  200  140\n",
              "3  4월  130  170"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5d4bc4ba-2536-47ba-a1bf-0ad3a606d3b5\" class=\"colab-df-container\">\n",
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              "<style scoped>\n",
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              "        vertical-align: middle;\n",
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              "\n",
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              "</style>\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>판매월</th>\n",
              "      <th>제품a</th>\n",
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              "      <th>0</th>\n",
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              "      <td>2월</td>\n",
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              "      <th>2</th>\n",
              "      <td>3월</td>\n",
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              "      <td>140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4월</td>\n",
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              "      <td>170</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5d4bc4ba-2536-47ba-a1bf-0ad3a606d3b5')\"\n",
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              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "\n",
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              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-5d4bc4ba-2536-47ba-a1bf-0ad3a606d3b5 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-5d4bc4ba-2536-47ba-a1bf-0ad3a606d3b5');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-fdb8fc6d-1e21-4bba-ac2a-9536f7f6addd\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-fdb8fc6d-1e21-4bba-ac2a-9536f7f6addd')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-fdb8fc6d-1e21-4bba-ac2a-9536f7f6addd button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_a84114b7-7d14-4361-9247-08ff0a03866b\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_a_b')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_a84114b7-7d14-4361-9247-08ff0a03866b button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df_a_b');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_a_b",
              "summary": "{\n  \"name\": \"df_a_b\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"\\ud310\\ub9e4\\uc6d4\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"2\\uc6d4\",\n          \"4\\uc6d4\",\n          \"1\\uc6d4\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uc81c\\ud488a\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 42,\n        \"min\": 100,\n        \"max\": 200,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          150,\n          130,\n          100\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uc81c\\ud488b\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 35,\n        \"min\": 90,\n        \"max\": 170,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          110,\n          170,\n          90\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_c_d=pd.DataFrame({'판매월':['1월','2월','3월','4월'],'제품c':[112,141,203,134],'제품d':[90,110,140,170]})\n",
        "df_c_d"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "FvwauM3VoIQK",
        "outputId": "85e5ede5-5f26-496d-e8e1-f0240cf1f1a3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  판매월  제품c  제품d\n",
              "0  1월  112   90\n",
              "1  2월  141  110\n",
              "2  3월  203  140\n",
              "3  4월  134  170"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-55a44e29-dd5e-4103-ad24-09f17d74ae29\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>판매월</th>\n",
              "      <th>제품c</th>\n",
              "      <th>제품d</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1월</td>\n",
              "      <td>112</td>\n",
              "      <td>90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2월</td>\n",
              "      <td>141</td>\n",
              "      <td>110</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3월</td>\n",
              "      <td>203</td>\n",
              "      <td>140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4월</td>\n",
              "      <td>134</td>\n",
              "      <td>170</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-55a44e29-dd5e-4103-ad24-09f17d74ae29')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-55a44e29-dd5e-4103-ad24-09f17d74ae29 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-55a44e29-dd5e-4103-ad24-09f17d74ae29');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-f246b16d-86d4-484a-88dc-9a45132fbf16\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f246b16d-86d4-484a-88dc-9a45132fbf16')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
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              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df_c_d');\n",
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              "\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_c_d",
              "summary": "{\n  \"name\": \"df_c_d\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"\\ud310\\ub9e4\\uc6d4\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"2\\uc6d4\",\n          \"4\\uc6d4\",\n          \"1\\uc6d4\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uc81c\\ud488c\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 39,\n        \"min\": 112,\n        \"max\": 203,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          141,\n          134,\n          112\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uc81c\\ud488d\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 35,\n        \"min\": 90,\n        \"max\": 170,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          110,\n          170,\n          90\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_a_b.merge(df_c_d)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "z-_h9_juodMN",
        "outputId": "7bf11fa8-3aa8-4659-fd0f-0fbf0e6ae4f5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  판매월  제품a  제품b  제품c  제품d\n",
              "0  1월  100   90  112   90\n",
              "1  2월  150  110  141  110\n",
              "2  3월  200  140  203  140\n",
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              "        const element = document.querySelector('#df-5d9dc420-67d3-4dcb-9648-1bd26d73ba7a');\n",
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              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
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              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "\n",
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              "    async function quickchart(key) {\n",
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              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
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              "            'suggestCharts', [key], {});\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "    (() => {\n",
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              "\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df_a_b\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"\\ud310\\ub9e4\\uc6d4\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"2\\uc6d4\",\n          \"4\\uc6d4\",\n          \"1\\uc6d4\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uc81c\\ud488a\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 42,\n        \"min\": 100,\n        \"max\": 200,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          150,\n          130,\n          100\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uc81c\\ud488b\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 35,\n        \"min\": 90,\n        \"max\": 170,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          110,\n          170,\n          90\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uc81c\\ud488c\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 39,\n        \"min\": 112,\n        \"max\": 203,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          141,\n          134,\n          112\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"\\uc81c\\ud488d\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 35,\n        \"min\": 90,\n        \"max\": 170,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          110,\n          170,\n          90\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_left=pd.DataFrame({'key':['A','B','C'],'left':[1,2,3]})\n",
        "df_left"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "kvno8mahohLd",
        "outputId": "93ff1f03-1fd0-417c-8ee9-351a92c4b2cb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  key  left\n",
              "0   A     1\n",
              "1   B     2\n",
              "2   C     3"
            ],
            "text/html": [
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              "    <div class=\"colab-df-buttons\">\n",
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              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6c3209b5-db82-4523-9dc8-49d2ff2b28d7')\"\n",
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              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-6c3209b5-db82-4523-9dc8-49d2ff2b28d7 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-6c3209b5-db82-4523-9dc8-49d2ff2b28d7');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-369c6330-33b0-48a2-bfa8-2564235ebf03\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-369c6330-33b0-48a2-bfa8-2564235ebf03')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-369c6330-33b0-48a2-bfa8-2564235ebf03 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_61800494-2609-4b31-8b88-5205861dc1be\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_left')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_61800494-2609-4b31-8b88-5205861dc1be button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df_left');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_left",
              "summary": "{\n  \"name\": \"df_left\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"key\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"A\",\n          \"B\",\n          \"C\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"left\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 1,\n        \"max\": 3,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          1,\n          2,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_right=pd.DataFrame({'key':['A','B','D'],'right':[4,5,6]})\n",
        "df_right"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "JZ_jkbhjp6Sq",
        "outputId": "16be203b-6a82-43b1-809c-728782c7fa9b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  key  right\n",
              "0   A      4\n",
              "1   B      5\n",
              "2   D      6"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b5ad1e6f-3c3f-4eb9-bfde-602a1c26d0c9\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>key</th>\n",
              "      <th>right</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>B</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>D</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b5ad1e6f-3c3f-4eb9-bfde-602a1c26d0c9')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-b5ad1e6f-3c3f-4eb9-bfde-602a1c26d0c9 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-b5ad1e6f-3c3f-4eb9-bfde-602a1c26d0c9');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-a081ed5a-1271-448a-b84b-1477c06e4a4e\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-a081ed5a-1271-448a-b84b-1477c06e4a4e')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
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              "    async function quickchart(key) {\n",
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              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-a081ed5a-1271-448a-b84b-1477c06e4a4e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_6183a968-28ef-4ecd-9300-6112635f33a2\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_right')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_6183a968-28ef-4ecd-9300-6112635f33a2 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df_right');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_right",
              "summary": "{\n  \"name\": \"df_right\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"key\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"A\",\n          \"B\",\n          \"D\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"right\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 4,\n        \"max\": 6,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          4,\n          5,\n          6\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_left.merge(df_right,how='left',on='key')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "h-_84Q_zqJNY",
        "outputId": "9563f830-3db6-43dd-f27b-cfbd2a634065"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  key  left  right\n",
              "0   A     1    4.0\n",
              "1   B     2    5.0\n",
              "2   C     3    NaN"
            ],
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              "      <td>3</td>\n",
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              "\n",
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              "\n",
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              "        document.querySelector('#df-c9c18ac1-e856-4856-b133-34845e1addbf button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-c9c18ac1-e856-4856-b133-34845e1addbf');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        docLink.innerHTML = docLinkHtml;\n",
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              "\n",
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              "\n",
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              "    width: 32px;\n",
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              "\n",
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              "\n",
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              "  .colab-df-quickchart-complete:disabled:hover {\n",
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              "\n",
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              "    border: 2px solid var(--fill-color);\n",
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              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-318337a9-3726-440a-9521-72c5efe19553 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df_left\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"key\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"A\",\n          \"B\",\n          \"C\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"left\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 1,\n        \"max\": 3,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          1,\n          2,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"right\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7071067811865476,\n        \"min\": 4.0,\n        \"max\": 5.0,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          5.0,\n          4.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from typing_extensions import ClassVar\n",
        "%%writefile C:\\myPyCode\\datasea_rain1.csv\n",
        "연도,동해,남해,서해,전체\n",
        "1996,17.4629,17.2288,14.436,15.9067\n",
        "1997,17.4116,17.4092,14.8248,16.1526\n",
        "1998,17.5944,18.011,15.2512,16.6044\n",
        "1999,18.1495,18.3175,144.8979,16.6284\n",
        "2000,17.9288,18.1766,15.0504,16.6178"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qBJNoGaGqRJL",
        "outputId": "41ba432c-6f28-4d6f-db35-f7a26764e56f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "UsageError: Line magic function `%%writefile` not found.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_WH=pd.DataFrame({'Weight':[62,67,55,74],'Height':[165,177,160,180]},index=['ID_1','ID_2','ID_3','ID_4'])\n",
        "df_WH.index.nmae='User'\n",
        "df_WH"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "6f9KwvA5rvcj",
        "outputId": "bdd1279f-682d-4c45-bbd6-1e7ddd2eb5cf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Weight  Height\n",
              "ID_1      62     165\n",
              "ID_2      67     177\n",
              "ID_3      55     160\n",
              "ID_4      74     180"
            ],
            "text/html": [
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
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              "      <th></th>\n",
              "      <th>Weight</th>\n",
              "      <th>Height</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>ID_1</th>\n",
              "      <td>62</td>\n",
              "      <td>165</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ID_2</th>\n",
              "      <td>67</td>\n",
              "      <td>177</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ID_3</th>\n",
              "      <td>55</td>\n",
              "      <td>160</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ID_4</th>\n",
              "      <td>74</td>\n",
              "      <td>180</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e468a2de-cd49-4cc2-b01e-ac9d8975e3bc')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-e468a2de-cd49-4cc2-b01e-ac9d8975e3bc button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-e468a2de-cd49-4cc2-b01e-ac9d8975e3bc');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-f15dca6b-4ec8-4561-a917-8ffc9a918be0\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f15dca6b-4ec8-4561-a917-8ffc9a918be0')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-f15dca6b-4ec8-4561-a917-8ffc9a918be0 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_b1d1d542-6fda-46c0-ba68-9b1656def406\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_WH')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_b1d1d542-6fda-46c0-ba68-9b1656def406 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df_WH');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_WH",
              "summary": "{\n  \"name\": \"df_WH\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"Weight\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8,\n        \"min\": 55,\n        \"max\": 74,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          67,\n          74,\n          62\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Height\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 9,\n        \"min\": 160,\n        \"max\": 180,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          177,\n          180,\n          165\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bmi=df_WH['Weight']/(df_WH['Height']/100)**2\n",
        "bmi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JqhBopwouFB9",
        "outputId": "4af3e339-757c-45a9-b66a-156a07a45775"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ID_1    22.773186\n",
              "ID_2    21.385936\n",
              "ID_3    21.484375\n",
              "ID_4    22.839506\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_WH['BMI']=bmi\n",
        "df_WH"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "1fG5pxBhulgi",
        "outputId": "1a4b5c78-7001-4482-bbfd-367f9bfc71c4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Weight  Height        BMI\n",
              "ID_1      62     165  22.773186\n",
              "ID_2      67     177  21.385936\n",
              "ID_3      55     160  21.484375\n",
              "ID_4      74     180  22.839506"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8b38c88f-d9d4-4ca9-8609-74fdde8ebc22\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Weight</th>\n",
              "      <th>Height</th>\n",
              "      <th>BMI</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>ID_1</th>\n",
              "      <td>62</td>\n",
              "      <td>165</td>\n",
              "      <td>22.773186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ID_2</th>\n",
              "      <td>67</td>\n",
              "      <td>177</td>\n",
              "      <td>21.385936</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ID_3</th>\n",
              "      <td>55</td>\n",
              "      <td>160</td>\n",
              "      <td>21.484375</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ID_4</th>\n",
              "      <td>74</td>\n",
              "      <td>180</td>\n",
              "      <td>22.839506</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8b38c88f-d9d4-4ca9-8609-74fdde8ebc22')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-8b38c88f-d9d4-4ca9-8609-74fdde8ebc22 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-8b38c88f-d9d4-4ca9-8609-74fdde8ebc22');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-e1f0b3e0-39dc-4f21-a3d9-bbc6934e1fdc\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e1f0b3e0-39dc-4f21-a3d9-bbc6934e1fdc')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
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              "     width=\"24px\">\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-e1f0b3e0-39dc-4f21-a3d9-bbc6934e1fdc button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_19472ca5-5ea4-4b45-bfa4-866e6925aa7f\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_WH')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_19472ca5-5ea4-4b45-bfa4-866e6925aa7f button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df_WH');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_WH",
              "summary": "{\n  \"name\": \"df_WH\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"Weight\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8,\n        \"min\": 55,\n        \"max\": 74,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          67,\n          74,\n          62\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Height\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 9,\n        \"min\": 160,\n        \"max\": 180,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          177,\n          180,\n          165\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"BMI\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7931388993711808,\n        \"min\": 21.38593635289987,\n        \"max\": 22.839506172839506,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          21.38593635289987,\n          22.839506172839506,\n          22.77318640955005\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_WH.to_csv('C:/myPyCode/data/save_DataFrame.csv')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "slLsSdAwuvPi",
        "outputId": "1d5cd012-c55e-4be2-bec8-d921633b655b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "OSError",
          "evalue": "Cannot save file into a non-existent directory: 'C:/myPyCode/data'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-40-9ff292525c0f>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf_WH\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'C:/myPyCode/data/save_DataFrame.csv'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mto_csv\u001b[0;34m(self, path_or_buf, sep, na_rep, float_format, columns, header, index, index_label, mode, encoding, compression, quoting, quotechar, lineterminator, chunksize, date_format, doublequote, escapechar, decimal, errors, storage_options)\u001b[0m\n\u001b[1;32m   3770\u001b[0m         )\n\u001b[1;32m   3771\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3772\u001b[0;31m         return DataFrameRenderer(formatter).to_csv(\n\u001b[0m\u001b[1;32m   3773\u001b[0m             \u001b[0mpath_or_buf\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3774\u001b[0m             \u001b[0mlineterminator\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlineterminator\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/formats/format.py\u001b[0m in \u001b[0;36mto_csv\u001b[0;34m(self, path_or_buf, encoding, sep, columns, index_label, mode, compression, quoting, quotechar, lineterminator, chunksize, date_format, doublequote, escapechar, errors, storage_options)\u001b[0m\n\u001b[1;32m   1184\u001b[0m             \u001b[0mformatter\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfmt\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1185\u001b[0m         )\n\u001b[0;32m-> 1186\u001b[0;31m         \u001b[0mcsv_formatter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1187\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1188\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcreated_buffer\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/formats/csvs.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    238\u001b[0m         \"\"\"\n\u001b[1;32m    239\u001b[0m         \u001b[0;31m# apply compression and byte/text conversion\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 240\u001b[0;31m         with get_handle(\n\u001b[0m\u001b[1;32m    241\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    242\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/common.py\u001b[0m in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m    735\u001b[0m     \u001b[0;31m# Only for write methods\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    736\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;34m\"r\"\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmode\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mis_path\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 737\u001b[0;31m         \u001b[0mcheck_parent_directory\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    738\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    739\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mcompression\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/common.py\u001b[0m in \u001b[0;36mcheck_parent_directory\u001b[0;34m(path)\u001b[0m\n\u001b[1;32m    598\u001b[0m     \u001b[0mparent\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparent\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    599\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mparent\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_dir\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 600\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mOSError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mrf\"Cannot save file into a non-existent directory: '{parent}'\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    601\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    602\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mOSError\u001b[0m: Cannot save file into a non-existent directory: 'C:/myPyCode/data'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!type C:\\myPyCode\\data\\save_DataFrame.csv"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2QPpssWdvSmq",
        "outputId": "d2336115-8c39-434f-bbde-3709e682aa61"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/bin/bash: line 1: type: C:myPyCodedatasave_DataFrame.csv: not found\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "zW_zYwNvvfmR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data1=[10,14,19,20,25]\n",
        "plt.plot(data1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 448
        },
        "id": "3h-x2Eo-wsAz",
        "outputId": "1f1e5f76-a6e2-479c-86b2-431cf6a3e67a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7d6660d78850>]"
            ]
          },
          "metadata": {},
          "execution_count": 43
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(data1)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "9psUdo3qxU1R",
        "outputId": "11dff16a-d4d4-402b-a104-75e84e31ef90"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%matplotlib qt\n",
        "plt.plot(data1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 533
        },
        "id": "bnSvvE4lxriA",
        "outputId": "45e90b44-66a2-4810-e42d-540caa4616fd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ImportError",
          "evalue": "Failed to import any of the following Qt binding modules: PyQt6, PySide6, PyQt5, PySide2",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-48-a2f4185b1ed8>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_line_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'matplotlib'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'qt'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mrun_line_magic\u001b[0;34m(self, magic_name, line, _stack_depth)\u001b[0m\n\u001b[1;32m   2416\u001b[0m                 \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'local_ns'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_local_scope\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstack_depth\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2417\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuiltin_trap\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2418\u001b[0;31m                 \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2419\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2420\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<decorator-gen-101>\u001b[0m in \u001b[0;36mmatplotlib\u001b[0;34m(self, line)\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/magic.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(f, *a, **k)\u001b[0m\n\u001b[1;32m    185\u001b[0m     \u001b[0;31m# but it's overkill for just that one bit of state.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    186\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mmagic_deco\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 187\u001b[0;31m         \u001b[0mcall\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    188\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    189\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcallable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/magics/pylab.py\u001b[0m in \u001b[0;36mmatplotlib\u001b[0;34m(self, line)\u001b[0m\n\u001b[1;32m     97\u001b[0m             \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Available matplotlib backends: %s\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mbackends_list\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     98\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 99\u001b[0;31m             \u001b[0mgui\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbackend\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshell\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0menable_matplotlib\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgui\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlower\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgui\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgui\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    100\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_show_matplotlib_backend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgui\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbackend\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    101\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/ipykernel/zmqshell.py\u001b[0m in \u001b[0;36menable_matplotlib\u001b[0;34m(self, gui)\u001b[0m\n\u001b[1;32m    599\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    600\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0menable_matplotlib\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgui\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 601\u001b[0;31m         \u001b[0mgui\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbackend\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mZMQInteractiveShell\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0menable_matplotlib\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgui\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    602\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    603\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36menable_matplotlib\u001b[0;34m(self, gui)\u001b[0m\n\u001b[1;32m   3645\u001b[0m                 \u001b[0mgui\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbackend\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfind_gui_and_backend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpylab_gui_select\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3646\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3647\u001b[0;31m         \u001b[0mpt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mactivate_matplotlib\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbackend\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3648\u001b[0m         \u001b[0mconfigure_inline_support\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbackend\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3649\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py\u001b[0m in \u001b[0;36mactivate_matplotlib\u001b[0;34m(backend)\u001b[0m\n\u001b[1;32m    357\u001b[0m     \u001b[0;32mfrom\u001b[0m \u001b[0mmatplotlib\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    358\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 359\u001b[0;31m     \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mswitch_backend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbackend\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    360\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    361\u001b[0m     \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_needmain\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mswitch_backend\u001b[0;34m(newbackend)\u001b[0m\n\u001b[1;32m    269\u001b[0m     \u001b[0mold_backend\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getitem__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrcParams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'backend'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    270\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 271\u001b[0;31m     backend_mod = importlib.import_module(\n\u001b[0m\u001b[1;32m    272\u001b[0m         cbook._backend_module_name(newbackend))\n\u001b[1;32m    273\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.10/importlib/__init__.py\u001b[0m in \u001b[0;36mimport_module\u001b[0;34m(name, package)\u001b[0m\n\u001b[1;32m    124\u001b[0m                 \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    125\u001b[0m             \u001b[0mlevel\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 126\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_bootstrap\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_gcd_import\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpackage\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    127\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    128\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.10/importlib/_bootstrap.py\u001b[0m in \u001b[0;36m_gcd_import\u001b[0;34m(name, package, level)\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.10/importlib/_bootstrap.py\u001b[0m in \u001b[0;36m_find_and_load\u001b[0;34m(name, import_)\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.10/importlib/_bootstrap.py\u001b[0m in \u001b[0;36m_find_and_load_unlocked\u001b[0;34m(name, import_)\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.10/importlib/_bootstrap.py\u001b[0m in \u001b[0;36m_load_unlocked\u001b[0;34m(spec)\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.10/importlib/_bootstrap_external.py\u001b[0m in \u001b[0;36mexec_module\u001b[0;34m(self, module)\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.10/importlib/_bootstrap.py\u001b[0m in \u001b[0;36m_call_with_frames_removed\u001b[0;34m(f, *args, **kwds)\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/matplotlib/backends/backend_qt5agg.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mbackends\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_QT_FORCE_QT5_BINDING\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m from .backend_qtagg import (    # noqa: F401, E402 # pylint: disable=W0611\n\u001b[0m\u001b[1;32m      8\u001b[0m     \u001b[0m_BackendQTAgg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mFigureCanvasQTAgg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mFigureManagerQT\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mNavigationToolbar2QT\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m     FigureCanvasAgg, FigureCanvasQT)\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/matplotlib/backends/backend_qtagg.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtransforms\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mBbox\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mqt_compat\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mQT_API\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_enum\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     10\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mbackend_agg\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mFigureCanvasAgg\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mbackend_qt\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mQtCore\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mQtGui\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_BackendQT\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mFigureCanvasQT\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/matplotlib/backends/qt_compat.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m    133\u001b[0m         \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    134\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 135\u001b[0;31m         raise ImportError(\n\u001b[0m\u001b[1;32m    136\u001b[0m             \u001b[0;34m\"Failed to import any of the following Qt binding modules: {}\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    137\u001b[0m             .format(\", \".join(_ETS.values())))\n",
            "\u001b[0;31mImportError\u001b[0m: Failed to import any of the following Qt binding modules: PyQt6, PySide6, PyQt5, PySide2",
            "",
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0;32m\nNOTE: If your import is failing due to a missing package, you can\nmanually install dependencies using either !pip or !apt.\n\nTo view examples of installing some common dependencies, click the\n\"Open Examples\" button below.\n\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n"
          ],
          "errorDetails": {
            "actions": [
              {
                "action": "open_url",
                "actionText": "Open Examples",
                "url": "/notebooks/snippets/importing_libraries.ipynb"
              }
            ]
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%matplotlib inline\n",
        "plt.plot(data1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 448
        },
        "id": "PlI_Ov23x2rQ",
        "outputId": "66345f3b-4b18-45b8-d422-e226b8eac31f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7d6660d266e0>]"
            ]
          },
          "metadata": {},
          "execution_count": 50
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "x=np.arrange(-4.5,5,0.5)\n",
        "y=2*x**2\n",
        "[x,y]\n",
        "plt.plot(x,y)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 346
        },
        "id": "MS6z1JJ2yAux",
        "outputId": "5d5198ac-8a10-4956-f3dc-947a50608f9b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "AttributeError",
          "evalue": "module 'numpy' has no attribute 'arrange'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-53-abe31dd8278d>\u001b[0m in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m4.5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0.5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/numpy/__init__.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(attr)\u001b[0m\n\u001b[1;32m    326\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Tester was removed in NumPy 1.25.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    327\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 328\u001b[0;31m         raise AttributeError(\"module {!r} has no attribute \"\n\u001b[0m\u001b[1;32m    329\u001b[0m                              \"{!r}\".format(__name__, attr))\n\u001b[1;32m    330\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: module 'numpy' has no attribute 'arrange'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "x=np.arrange(-5,5,0.1)\n",
        "y1=x**2-2\n",
        "y2=20*np.cos(x)**2\n",
        "plt.figure(1)\n",
        "plt.plot(x,y1)\n",
        "plt.figure(2)\n",
        "plt.plot(x,y2)\n",
        "plt.figure(2)\n",
        "plt.clf()\n",
        "plt.plot(x,y1)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "jGtxPbQXyQoA",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 346
        },
        "outputId": "41ff081e-8edd-4670-ca61-69d4e564f13e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "AttributeError",
          "evalue": "module 'numpy' has no attribute 'arrange'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-55-fd78603f4ce9>\u001b[0m in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0.1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0my1\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0my2\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m20\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcos\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/numpy/__init__.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(attr)\u001b[0m\n\u001b[1;32m    326\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Tester was removed in NumPy 1.25.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    327\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 328\u001b[0;31m         raise AttributeError(\"module {!r} has no attribute \"\n\u001b[0m\u001b[1;32m    329\u001b[0m                              \"{!r}\".format(__name__, attr))\n\u001b[1;32m    330\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: module 'numpy' has no attribute 'arrange'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "x=np.arrange(0,5,1)\n",
        "y1=x\n",
        "y2=x+1\n",
        "y3=x+2\n",
        "y=x+3\n",
        "\n",
        "plt.plot(x,y1,'>--r',x,y2,'s-g',x,y3,'d:b',x,y4,'-.Xc')\n",
        "plt.legend(['data1','data2','data3','data4'])\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 346
        },
        "id": "wf_Sug-614ou",
        "outputId": "2c34da11-43bd-42a6-da90-732df450b4da"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "AttributeError",
          "evalue": "module 'numpy' has no attribute 'arrange'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-57-fc678481e1cd>\u001b[0m in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0my1\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0my2\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0my3\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/numpy/__init__.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(attr)\u001b[0m\n\u001b[1;32m    326\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Tester was removed in NumPy 1.25.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    327\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 328\u001b[0;31m         raise AttributeError(\"module {!r} has no attribute \"\n\u001b[0m\u001b[1;32m    329\u001b[0m                              \"{!r}\".format(__name__, attr))\n\u001b[1;32m    330\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: module 'numpy' has no attribute 'arrange'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "city=['서울','인천','대구','대전','울산','부산','광주']\n",
        "lat=[37.56,37.45,36.35,35.87,35.53,35.18,35.16]\n",
        "lon=[126.97,126.70,127.38,128.60,129.31,129.07,126.85]\n",
        "pop_den=[16154,2751,2839,2790,1099,4454,2995]\n",
        "size=np.array(pop_den)*0.2\n",
        "colors=['r','g','b','c','m','k','y']\n",
        "plt.scatter(lon,lat,s=size,c=colors,alpha=0.5)\n",
        "plt.xlabel=('경도')\n",
        "plt.ylabel=('위도')\n",
        "plt.title('지역별 인구밀도(2017)')\n",
        "for x,y,name in zip(lon,lat,city):\n",
        "  plt.text(x,y,name)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 219
        },
        "id": "qMQePbDlD2mD",
        "outputId": "c66be721-e287-4b9d-9a99-08c8eb7a7e71"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "name 'plt' is not defined",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-2-e9e86d7ff50f>\u001b[0m in \u001b[0;36m<cell line: 8>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0msize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpop_den\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0;36m0.2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0mcolors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'r'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'g'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'b'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'c'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'm'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'k'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'y'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscatter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlon\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlat\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msize\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcolors\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0malpha\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      9\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'경도'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'위도'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mNameError\u001b[0m: name 'plt' is not defined"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fruit=['사과','바나나','딸기','오렌지','포도']\n",
        "result=[7,6,3,2,2]\n",
        "import matplotlib.pyplot as plt\n",
        "plt.pie(result)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "HDPRvuSA1mgk",
        "outputId": "7a792f8a-8526-40bb-e290-b3d967271010"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(5,5))\n",
        "plt.pie(result)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 422
        },
        "id": "zm9MrOYgGuAM",
        "outputId": "0c3410af-3284-4055-dbb5-1a25833beb0d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "explode_value=(0.1,0,0,0,0)\n",
        "plt.figure(figsize=(5,5))\n",
        "plt.pie(result,labels=fruit,autopct='%.1f%%',startangle=90,counterclock=False,explode=explode_value,shadow=True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 821
        },
        "id": "nKaCTn3BG-c0",
        "outputId": "210ae701-4eb8-4e54-a2d2-f5e78a73c4c7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 49324 (\\N{HANGUL SYLLABLE SA}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 44284 (\\N{HANGUL SYLLABLE GWA}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 48148 (\\N{HANGUL SYLLABLE BA}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 45208 (\\N{HANGUL SYLLABLE NA}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 46392 (\\N{HANGUL SYLLABLE DDAL}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 44592 (\\N{HANGUL SYLLABLE GI}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 50724 (\\N{HANGUL SYLLABLE O}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 47116 (\\N{HANGUL SYLLABLE REN}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 51648 (\\N{HANGUL SYLLABLE JI}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 54252 (\\N{HANGUL SYLLABLE PO}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 46020 (\\N{HANGUL SYLLABLE DO}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib as np\n",
        "mpl.rcParams['figure.figsize']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 164
        },
        "id": "lx_fcFFvIhxQ",
        "outputId": "f2e8468b-e731-489f-b98a-f86f71c9a598"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "name 'mpl' is not defined",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-13-d869509eed17>\u001b[0m in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mmpl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrcParams\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'figure.figsize'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m: name 'mpl' is not defined"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "s1=pd.Series([1,2,3,4,5,6,7,8,9,10])\n",
        "s1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y6WnUSQpJ-AI",
        "outputId": "c079234d-fd0b-4430-b007-9206e745d444"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0     1\n",
              "1     2\n",
              "2     3\n",
              "3     4\n",
              "4     5\n",
              "5     6\n",
              "6     7\n",
              "7     8\n",
              "8     9\n",
              "9    10\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "s1.plot()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "q0Q4BiRoTwQH",
        "outputId": "bebc01de-04b6-4135-c224-42724369de8c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "s1.plot(grid=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 448
        },
        "id": "4EFsYFLNUCmT",
        "outputId": "4881ede5-ebad-4aec-bd02-4f6ecf46f00c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_rain=pd.read_csv('C:/myPyCode/data/sea_rain1.csv',index_col=\"연도\")\n",
        "df_rain"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 315
        },
        "id": "Lq0dmbj5ddIY",
        "outputId": "b20e0dbc-b603-4255-a02e-255d8172a4a0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "FileNotFoundError",
          "evalue": "[Errno 2] No such file or directory: 'C:/myPyCode/data/sea_rain1.csv'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-22-fcac7037fe52>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf_rain\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'C:/myPyCode/data/sea_rain1.csv'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mindex_col\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"연도\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mdf_rain\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/parsers/readers.py\u001b[0m in \u001b[0;36mread_csv\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend)\u001b[0m\n\u001b[1;32m    910\u001b[0m     \u001b[0mkwds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkwds_defaults\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    911\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 912\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    913\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    914\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/parsers/readers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    575\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    576\u001b[0m     \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 577\u001b[0;31m     \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    578\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    579\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/parsers/readers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m   1405\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1406\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhandles\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mIOHandles\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1407\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1408\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1409\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/parsers/readers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, f, engine)\u001b[0m\n\u001b[1;32m   1659\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0;34m\"b\"\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1660\u001b[0m                     \u001b[0mmode\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;34m\"b\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1661\u001b[0;31m             self.handles = get_handle(\n\u001b[0m\u001b[1;32m   1662\u001b[0m                 \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1663\u001b[0m                 \u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/common.py\u001b[0m in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m    857\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mioargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mencoding\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;34m\"b\"\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mioargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    858\u001b[0m             \u001b[0;31m# Encoding\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 859\u001b[0;31m             handle = open(\n\u001b[0m\u001b[1;32m    860\u001b[0m                 \u001b[0mhandle\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    861\u001b[0m                 \u001b[0mioargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'C:/myPyCode/data/sea_rain1.csv'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import pandas as np\n",
        "math=[76,82,84,83,90,86,85,92,72,71,100,87,81,76,94,78,81,60,79,69,74,87,82,68,79]\n",
        "df_math=pd.DataFrame(math,columns=['Student'])\n",
        "math_hist=df_math.plot.hist(bins=8,grid=True)\n",
        "math_hist.set_xlabel(\"시험점수\")\n",
        "math_hist.set.ylabel(\"도수\")\n",
        "math_hist.set.title(\"수학 시험의 히스토그램\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 941
        },
        "id": "LxSHoUGxdh91",
        "outputId": "5f91a9b3-338b-4911-e976-6c5b9260c3fd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "AttributeError",
          "evalue": "'function' object has no attribute 'ylabel'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-24-342f942faa4b>\u001b[0m in \u001b[0;36m<cell line: 7>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mmath_hist\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdf_math\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbins\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mgrid\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mmath_hist\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_xlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"시험점수\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mmath_hist\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"도수\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      8\u001b[0m \u001b[0mmath_hist\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"수학 시험의 히스토그램\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: 'function' object has no attribute 'ylabel'"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/IPython/core/events.py:89: UserWarning: Glyph 49884 (\\N{HANGUL SYLLABLE SI}) missing from current font.\n",
            "  func(*args, **kwargs)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/events.py:89: UserWarning: Glyph 54744 (\\N{HANGUL SYLLABLE HEOM}) missing from current font.\n",
            "  func(*args, **kwargs)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/events.py:89: UserWarning: Glyph 51216 (\\N{HANGUL SYLLABLE JEOM}) missing from current font.\n",
            "  func(*args, **kwargs)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/events.py:89: UserWarning: Glyph 49688 (\\N{HANGUL SYLLABLE SU}) missing from current font.\n",
            "  func(*args, **kwargs)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 49884 (\\N{HANGUL SYLLABLE SI}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 54744 (\\N{HANGUL SYLLABLE HEOM}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 51216 (\\N{HANGUL SYLLABLE JEOM}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n",
            "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 49688 (\\N{HANGUL SYLLABLE SU}) missing from current font.\n",
            "  fig.canvas.print_figure(bytes_io, **kw)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "excel_data_files=['C:/myPyCode/data/담당자별_판매량_Andy사원.xlsx','C:/myPyCode/data/담당자별_판매량_Becky사원.xlsx','C:/myPyCode/data/담당자별_판매량_Chris사원.xlsx']"
      ],
      "metadata": {
        "id": "x5QfQXl5xTVT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "total_data=pd.DataFrame()"
      ],
      "metadata": {
        "id": "FoFBXNhtAbDG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "for f in excel_data_files:\n",
        "  df=pd.read_excel(f)\n",
        "  total_data=total_data.append(df)\n",
        "total_data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 370
        },
        "id": "1yQPXsePAeX_",
        "outputId": "07c16ae5-7b8e-479c-9c79-f359df466a07"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "FileNotFoundError",
          "evalue": "[Errno 2] No such file or directory: 'C:/myPyCode/data/담당자별_판매량_Andy사원.xlsx'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-28-f1a269af31ca>\u001b[0m in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpandas\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mexcel_data_files\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m   \u001b[0mdf\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_excel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m   \u001b[0mtotal_data\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtotal_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mtotal_data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/excel/_base.py\u001b[0m in \u001b[0;36mread_excel\u001b[0;34m(io, sheet_name, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, parse_dates, date_parser, date_format, thousands, decimal, comment, skipfooter, storage_options, dtype_backend)\u001b[0m\n\u001b[1;32m    476\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mio\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mExcelFile\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    477\u001b[0m         \u001b[0mshould_close\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 478\u001b[0;31m         \u001b[0mio\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mExcelFile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mio\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstorage_options\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstorage_options\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    479\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    480\u001b[0m         raise ValueError(\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/excel/_base.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, path_or_buffer, engine, storage_options)\u001b[0m\n\u001b[1;32m   1494\u001b[0m                 \u001b[0mext\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"xls\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1495\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1496\u001b[0;31m                 ext = inspect_excel_format(\n\u001b[0m\u001b[1;32m   1497\u001b[0m                     \u001b[0mcontent_or_path\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstorage_options\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstorage_options\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1498\u001b[0m                 )\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/excel/_base.py\u001b[0m in \u001b[0;36minspect_excel_format\u001b[0;34m(content_or_path, storage_options)\u001b[0m\n\u001b[1;32m   1369\u001b[0m         \u001b[0mcontent_or_path\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBytesIO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcontent_or_path\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1370\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1371\u001b[0;31m     with get_handle(\n\u001b[0m\u001b[1;32m   1372\u001b[0m         \u001b[0mcontent_or_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"rb\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstorage_options\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstorage_options\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mis_text\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1373\u001b[0m     ) as handle:\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/common.py\u001b[0m in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m    866\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    867\u001b[0m             \u001b[0;31m# Binary mode\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 868\u001b[0;31m             \u001b[0mhandle\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mioargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    869\u001b[0m         \u001b[0mhandles\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    870\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'C:/myPyCode/data/담당자별_판매량_Andy사원.xlsx'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import re\n",
        "file_name='C:/myPyCode/data/담당자별_판매량_Andy사원.xlsx'\n",
        "new_file_name=re.sub('xlsx','2.xlsx,file_name')\n",
        "new_file_name"
      ],
      "metadata": {
        "id": "7-wt1ENmAsgC",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 200
        },
        "outputId": "de483b15-3fdb-4626-bf55-9d33340bb427"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "TypeError",
          "evalue": "sub() missing 1 required positional argument: 'string'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-1-23d186eef040>\u001b[0m in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mre\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mfile_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'C:/myPyCode/data/담당자별_판매량_Andy사원.xlsx'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mnew_file_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mre\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'xlsx'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'2.xlsx,file_name'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0mnew_file_name\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mTypeError\u001b[0m: sub() missing 1 required positional argument: 'string'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "handbag_sum2=pd.DataFrame(handbag_total.sum(),columns=['합계'])\n",
        "handbag_sum2"
      ],
      "metadata": {
        "id": "H1sgUwkPeTY_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 164
        },
        "outputId": "6391e466-680e-4a58-e92f-9e97a6556428"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "name 'pd' is not defined",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-1-3737ab9697d8>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mhandbag_sum2\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhandbag_total\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'합계'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mhandbag_sum2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mNameError\u001b[0m: name 'pd' is not defined"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "df=pd.read_excel(\"C:/myPyCode/data/담당자별_판매량_통합.xlsx\")\n",
        "product_name='핸드백'\n",
        "handbag=df[(df['제품명']=product_name)]\n",
        "handbag_sum=pd.DataFrame(handbag.sum(axis=1),columns=['연간판매량'])\n",
        "handbag_total=handbag.join(handbag_sum)\n",
        "\n",
        "handbag_sum2=pd.DataFrame(handbag_total.sum(),columns=['합계'])\n",
        "handbag_total2=handbag_total.append(handbag_sum2.T)\n",
        "\n",
        "handbag_total2.loc['합계','제품명']=product_name\n",
        "handbag_total2.loc['합계','담당자']='전체'\n",
        "handbag_total2.loc['합계','지역']='전체'\n",
        "\n",
        "handbag_total2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 110
        },
        "id": "oVJkKj9uquH1",
        "outputId": "26f741b7-5df7-4f67-e3ce-8a2e86a11854"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "SyntaxError",
          "evalue": "cannot assign to subscript here. Maybe you meant '==' instead of '='? (<ipython-input-2-0015d4bbe255>, line 4)",
          "traceback": [
            "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-2-0015d4bbe255>\"\u001b[0;36m, line \u001b[0;32m4\u001b[0m\n\u001b[0;31m    handbag=df[(df['제품명']=product_name)]\u001b[0m\n\u001b[0m                ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m cannot assign to subscript here. Maybe you meant '==' instead of '='?\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "df_left=pd.DataFrame({'key':['A','B','C'],'left':[1,2,3]})\n",
        "df_right=pd.DataFrame({'key':['A','B','D'],'right':[4,5,6]})\n",
        "print(df_left)\n",
        "print(df_right)"
      ],
      "metadata": {
        "id": "qFL0HC_i6upU",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "064e111d-eb95-4302-aacd-b55ec6d58ff7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  key  left\n",
            "0   A     1\n",
            "1   B     2\n",
            "2   C     3\n",
            "  key  right\n",
            "0   A      4\n",
            "1   B      5\n",
            "2   D      6\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_right.merge(df_left,how='left',on='key')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "vL23E54Xh6vW",
        "outputId": "80e9291f-f487-469f-a416-ec51315ebe90"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  key  right  left\n",
              "0   A      4   1.0\n",
              "1   B      5   2.0\n",
              "2   D      6   NaN"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e3b88686-13e6-49ea-b19b-1d7f48300160\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>key</th>\n",
              "      <th>right</th>\n",
              "      <th>left</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A</td>\n",
              "      <td>4</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>B</td>\n",
              "      <td>5</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>D</td>\n",
              "      <td>6</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e3b88686-13e6-49ea-b19b-1d7f48300160')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-e3b88686-13e6-49ea-b19b-1d7f48300160 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-e3b88686-13e6-49ea-b19b-1d7f48300160');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-4b6edf1d-0a6a-4897-8b81-9ce5fb64a14b\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4b6edf1d-0a6a-4897-8b81-9ce5fb64a14b')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-4b6edf1d-0a6a-4897-8b81-9ce5fb64a14b button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df_right\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"key\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"A\",\n          \"B\",\n          \"D\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"right\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 4,\n        \"max\": 6,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          4,\n          5,\n          6\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"left\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7071067811865476,\n        \"min\": 1.0,\n        \"max\": 2.0,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          2.0,\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_right.merge(df_left,how='right',on='key')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "wLa-ClYoiIrK",
        "outputId": "c2cda8b4-fe55-4945-c5a7-d87623bf96de"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  key  right  left\n",
              "0   A    4.0     1\n",
              "1   B    5.0     2\n",
              "2   C    NaN     3"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-2ebf24aa-bf55-4a60-bfc2-08eb825f14ce\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>key</th>\n",
              "      <th>right</th>\n",
              "      <th>left</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>B</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>C</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2ebf24aa-bf55-4a60-bfc2-08eb825f14ce')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-2ebf24aa-bf55-4a60-bfc2-08eb825f14ce button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-2ebf24aa-bf55-4a60-bfc2-08eb825f14ce');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-0abb29de-a2d9-4ed7-845c-4871463cd34f\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0abb29de-a2d9-4ed7-845c-4871463cd34f')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-0abb29de-a2d9-4ed7-845c-4871463cd34f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df_right\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"key\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"A\",\n          \"B\",\n          \"C\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"right\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7071067811865476,\n        \"min\": 4.0,\n        \"max\": 5.0,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          5.0,\n          4.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"left\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 1,\n        \"max\": 3,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          1,\n          2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "RdbrYAuViYT5"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}