Assignment6_CS_202151160.ipynb

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          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ],
      "source": [
        "#CS312 - Data Analytics and Visualization\n",
        "#Assignment 6\n",
        "#Name: Snehal Nalawade\n",
        "#ID: 202151160\n",
        "\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Importing the necessary Libraries:"
      ],
      "metadata": {
        "id": "Vde-2Vd0n_NO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np"
      ],
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        "id": "T6vKbWAUn0T8"
      },
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      "outputs": []
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      "source": [
        "Reading Data:"
      ],
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        "id": "d9RxspFFoHaY"
      }
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    {
      "cell_type": "code",
      "source": [
        "female_population = pd.read_csv('/content/drive/MyDrive/DAV sem 6/population_of_female - population_of_female.csv')\n",
        "female_completion = pd.read_csv('/content/drive/MyDrive/DAV sem 6/primary_completion_rate_female - primary_completion_rate_female.csv')"
      ],
      "metadata": {
        "id": "ISNov7oioFwD"
      },
      "execution_count": null,
      "outputs": []
    },
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      "cell_type": "markdown",
      "source": [
        "1. Create a column named “average_rate” in “primary_completion_rate_female.csv” that contains the average (over years) completion rate for each country."
      ],
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        "id": "cqgCrOJoqTdb"
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      "source": [
        "female_completion['avgRate'] = female_completion.mean(axis=1, numeric_only=True)\n",
        "df1 = female_completion[['Country Name', 'avgRate']]\n",
        "df1.head()"
      ],
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              "                  Country Name    avgRate\n",
              "0                        Aruba  96.203056\n",
              "1  Africa Eastern and Southern  52.899081\n",
              "2                  Afghanistan  28.085734\n",
              "3   Africa Western and Central  54.108691\n",
              "4                       Angola  34.111267"
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              "      <td>Aruba</td>\n",
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              "      <td>Afghanistan</td>\n",
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              "summary": "{\n  \"name\": \"df1\",\n  \"rows\": 266,\n  \"fields\": [\n    {\n      \"column\": \"Country Name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 266,\n        \"samples\": [\n          \"OECD members\",\n          \"Japan\",\n          \"Lower middle income\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"avgRate\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 22.647980631719577,\n        \"min\": 13.0539159538,\n        \"max\": 109.9339920435294,\n        \"num_unique_values\": 243,\n        \"samples\": [\n          90.64363534571429,\n          64.2997655680392,\n          99.11556439538462\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
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      "source": [
        "2. Create a column named “Latest Population” in “population_of_female.csv” that contains the latest population of females in the country."
      ],
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        "id": "Nu2iPmw7qhuB"
      }
    },
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      "source": [
        "female_population['Latest Population'] = female_population.iloc[:,-1]\n",
        "female_population.head()"
      ],
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        "id": "pd_regDCqka6",
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            "text/plain": [
              "                  Country Name Country Code     Indicator Name  \\\n",
              "0                        Aruba          ABW  Population female   \n",
              "1  Africa Eastern and Southern          AFE  Population female   \n",
              "2                  Afghanistan          AFG  Population female   \n",
              "3   Africa Western and Central          AFW  Population female   \n",
              "4                       Angola          AGO  Population female   \n",
              "\n",
              "      Indicator Code        1960        1961        1962        1963  \\\n",
              "0  SP.POP.TOTL.FE.IN     27773.0     28380.0     28820.0     29218.0   \n",
              "1  SP.POP.TOTL.FE.IN  65853220.0  67606287.0  69457112.0  71375643.0   \n",
              "2  SP.POP.TOTL.FE.IN   4145945.0   4233771.0   4326881.0   4424511.0   \n",
              "3  SP.POP.TOTL.FE.IN  48802898.0  49850088.0  50928609.0  52044907.0   \n",
              "4  SP.POP.TOTL.FE.IN   2670229.0   2704394.0   2742689.0   2779473.0   \n",
              "\n",
              "         1964        1965  ...         2013         2014         2015  \\\n",
              "0     29570.0     29875.0  ...      53953.0      54403.0      54828.0   \n",
              "1  73386167.0  75478396.0  ...  287224786.0  295088995.0  303195759.0   \n",
              "2   4526691.0   4634341.0  ...   15594637.0   16172321.0   16682054.0   \n",
              "3  53196730.0  54389295.0  ...  192900081.0  198163527.0  203513873.0   \n",
              "4   2812590.0   2838939.0  ...   13252938.0   13746371.0   14248799.0   \n",
              "\n",
              "          2016         2017         2018         2019         2020  \\\n",
              "0      55224.0      55591.0      55935.0      56254.0      56373.0   \n",
              "1  311387262.0  319637226.0  328158974.0  336930831.0  345889729.0   \n",
              "2   17115346.0   17614722.0   18136922.0   18679089.0   19279930.0   \n",
              "3  208980433.0  214578994.0  220253839.0  226004857.0  231877590.0   \n",
              "4   14764575.0   15293335.0   15828040.0   16370553.0   16910989.0   \n",
              "\n",
              "          2021  Latest Population  \n",
              "0      56330.0            56330.0  \n",
              "1  354855082.0        354855082.0  \n",
              "2   19844584.0         19844584.0  \n",
              "3  237813580.0        237813580.0  \n",
              "4   17452283.0         17452283.0  \n",
              "\n",
              "[5 rows x 67 columns]"
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Country Name</th>\n",
              "      <th>Country Code</th>\n",
              "      <th>Indicator Name</th>\n",
              "      <th>Indicator Code</th>\n",
              "      <th>1960</th>\n",
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              "      <th>2021</th>\n",
              "      <th>Latest Population</th>\n",
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              "      <th>0</th>\n",
              "      <td>Aruba</td>\n",
              "      <td>ABW</td>\n",
              "      <td>Population female</td>\n",
              "      <td>SP.POP.TOTL.FE.IN</td>\n",
              "      <td>27773.0</td>\n",
              "      <td>28380.0</td>\n",
              "      <td>28820.0</td>\n",
              "      <td>29218.0</td>\n",
              "      <td>29570.0</td>\n",
              "      <td>29875.0</td>\n",
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              "      <td>53953.0</td>\n",
              "      <td>54403.0</td>\n",
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              "      <td>55591.0</td>\n",
              "      <td>55935.0</td>\n",
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              "      <td>56373.0</td>\n",
              "      <td>56330.0</td>\n",
              "      <td>56330.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Africa Eastern and Southern</td>\n",
              "      <td>AFE</td>\n",
              "      <td>Population female</td>\n",
              "      <td>SP.POP.TOTL.FE.IN</td>\n",
              "      <td>65853220.0</td>\n",
              "      <td>67606287.0</td>\n",
              "      <td>69457112.0</td>\n",
              "      <td>71375643.0</td>\n",
              "      <td>73386167.0</td>\n",
              "      <td>75478396.0</td>\n",
              "      <td>...</td>\n",
              "      <td>287224786.0</td>\n",
              "      <td>295088995.0</td>\n",
              "      <td>303195759.0</td>\n",
              "      <td>311387262.0</td>\n",
              "      <td>319637226.0</td>\n",
              "      <td>328158974.0</td>\n",
              "      <td>336930831.0</td>\n",
              "      <td>345889729.0</td>\n",
              "      <td>354855082.0</td>\n",
              "      <td>354855082.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>AFG</td>\n",
              "      <td>Population female</td>\n",
              "      <td>SP.POP.TOTL.FE.IN</td>\n",
              "      <td>4145945.0</td>\n",
              "      <td>4233771.0</td>\n",
              "      <td>4326881.0</td>\n",
              "      <td>4424511.0</td>\n",
              "      <td>4526691.0</td>\n",
              "      <td>4634341.0</td>\n",
              "      <td>...</td>\n",
              "      <td>15594637.0</td>\n",
              "      <td>16172321.0</td>\n",
              "      <td>16682054.0</td>\n",
              "      <td>17115346.0</td>\n",
              "      <td>17614722.0</td>\n",
              "      <td>18136922.0</td>\n",
              "      <td>18679089.0</td>\n",
              "      <td>19279930.0</td>\n",
              "      <td>19844584.0</td>\n",
              "      <td>19844584.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Africa Western and Central</td>\n",
              "      <td>AFW</td>\n",
              "      <td>Population female</td>\n",
              "      <td>SP.POP.TOTL.FE.IN</td>\n",
              "      <td>48802898.0</td>\n",
              "      <td>49850088.0</td>\n",
              "      <td>50928609.0</td>\n",
              "      <td>52044907.0</td>\n",
              "      <td>53196730.0</td>\n",
              "      <td>54389295.0</td>\n",
              "      <td>...</td>\n",
              "      <td>192900081.0</td>\n",
              "      <td>198163527.0</td>\n",
              "      <td>203513873.0</td>\n",
              "      <td>208980433.0</td>\n",
              "      <td>214578994.0</td>\n",
              "      <td>220253839.0</td>\n",
              "      <td>226004857.0</td>\n",
              "      <td>231877590.0</td>\n",
              "      <td>237813580.0</td>\n",
              "      <td>237813580.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Angola</td>\n",
              "      <td>AGO</td>\n",
              "      <td>Population female</td>\n",
              "      <td>SP.POP.TOTL.FE.IN</td>\n",
              "      <td>2670229.0</td>\n",
              "      <td>2704394.0</td>\n",
              "      <td>2742689.0</td>\n",
              "      <td>2779473.0</td>\n",
              "      <td>2812590.0</td>\n",
              "      <td>2838939.0</td>\n",
              "      <td>...</td>\n",
              "      <td>13252938.0</td>\n",
              "      <td>13746371.0</td>\n",
              "      <td>14248799.0</td>\n",
              "      <td>14764575.0</td>\n",
              "      <td>15293335.0</td>\n",
              "      <td>15828040.0</td>\n",
              "      <td>16370553.0</td>\n",
              "      <td>16910989.0</td>\n",
              "      <td>17452283.0</td>\n",
              "      <td>17452283.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 67 columns</p>\n",
              "</div>\n",
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              "                                                    [key], {});\n",
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              "\n",
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              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
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              "            'suggestCharts', [key], {});\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "female_population"
            }
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "3. What is the weighted average of “average_rate”? The weight should be calculated based on “latest population” of females in the country."
      ],
      "metadata": {
        "id": "POU1qMX4qm9X"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "wtAvg, sum = 0, 0\n",
        "for i in range(len(female_completion)):\n",
        "    if np.isnan(female_completion['avgRate'][i]):\n",
        "        continue\n",
        "    else:\n",
        "        wtAvg += female_completion['avgRate'][i] * female_population['Latest Population'][i]\n",
        "        sum += female_population['Latest Population'][i]\n",
        "wtAvg /= sum\n",
        "print(wtAvg)"
      ],
      "metadata": {
        "id": "eTMpi_MHqpli",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "edc0bde4-17fb-4297-d944-c6c93c8aaca8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "77.26494154546334\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "4. What is the Median of “average_rate”?"
      ],
      "metadata": {
        "id": "ZUsTbrSyqr-K"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "median = female_completion['avgRate'].median()\n",
        "print(median)"
      ],
      "metadata": {
        "id": "CbK7I8YSquUh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "51bfc0ff-71f1-40a5-f3f0-e256a22b560b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "90.96608239594593\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "5. What is the InterQuartile Range of “average_rate”?"
      ],
      "metadata": {
        "id": "l-zLcTrMqwim"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "q1, q3 = female_completion['avgRate'].quantile([.25,.75])\n",
        "iqr = q3-q1\n",
        "print(iqr)"
      ],
      "metadata": {
        "id": "d-emdLTxqzMQ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "62050685-dd8f-445d-dd4f-4bf614e9d9ce"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "29.470233932725478\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "6. What is the Variance of “average_rate”?"
      ],
      "metadata": {
        "id": "kwzqWiCpq1F-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "variance = female_completion['avgRate'].var()\n",
        "print(variance)"
      ],
      "metadata": {
        "id": "jPizBeX0q32q",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "99c0473c-9d86-44c3-bd43-41c565d50773"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "512.931026694745\n"
          ]
        }
      ]
    }
  ]
}