Uber Data Analysis.ipynb

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   "source": [
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "import matplotlib.pyplot as plt # data visualization\n",
    "import seaborn as sns # data visualization\n",
    "\n",
    "plt.style.use('ggplot') # styling graph"
   ]
  },
  {
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   "source": [
    "# Introduction"
   ]
  },
  {
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   "source": [
    "**This work is intentionally built for personal use, that is to exercise in data analysis and visualization.**\n",
    "\n",
    "Greetings and a warm welcome to my notebook. Within this dataset, I set out to explore and find answers to the following intriguing questions:\n",
    "\n",
    "- How many Uber trips occurred during the timestamp in the dataset?\n",
    "- What is the median for daily and monthly total trips?\n",
    "- How is the customer segment proportion?\n",
    "- How is the hourly trend for Uber trips?\n",
    "- How are the conditional probabilities of each segment ordering an Uber for each hour?\n",
    "- What are the favorite pick-up spots for each segment?\n",
    "- How is the daily trend for Uber trips?\n",
    "- How is the monthly trend for Uber trips?\n",
    "- Is there any specific characteristic of each segment based on their travel distance?\n",
    "- Is there any specific characteristic of each segment based on the travel duration?\n",
    "\n",
    "Your guidance and feedback are invaluable, and I look forward to learning and growing through your contributions. Thank you all, and here's to an enjoyable and enlightening read!"
   ]
  },
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   "source": [
    "# Data description\n",
    "\n",
    "- `START_DATE`: Timestamp that marks the start of the trip.\n",
    "- `END_DATE`: Timestamp that marks the end of the trip.\n",
    "- `CATEGORY`: Uber customer category.\n",
    "- `START`: Location that marks the start of the trip.\n",
    "- `STOP`: Location that marks the start of the trip.\n",
    "- `MILES`: Travel distance.\n",
    "- `PURPOSE`: Customer's purpose of ordering Uber."
   ]
  },
  {
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    "tags": []
   },
   "source": [
    "# Importing data"
   ]
  },
  {
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       "    .dataframe thead th {\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>START_DATE</th>\n",
       "      <th>END_DATE</th>\n",
       "      <th>CATEGORY</th>\n",
       "      <th>START</th>\n",
       "      <th>STOP</th>\n",
       "      <th>MILES</th>\n",
       "      <th>PURPOSE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01-01-2016 21:11</td>\n",
       "      <td>01-01-2016 21:17</td>\n",
       "      <td>Business</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>5.1</td>\n",
       "      <td>Meal/Entertain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01-02-2016 01:25</td>\n",
       "      <td>01-02-2016 01:37</td>\n",
       "      <td>Business</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01-02-2016 20:25</td>\n",
       "      <td>01-02-2016 20:38</td>\n",
       "      <td>Business</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>4.8</td>\n",
       "      <td>Errand/Supplies</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01-05-2016 17:31</td>\n",
       "      <td>01-05-2016 17:45</td>\n",
       "      <td>Business</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>4.7</td>\n",
       "      <td>Meeting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01-06-2016 14:42</td>\n",
       "      <td>01-06-2016 15:49</td>\n",
       "      <td>Business</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>West Palm Beach</td>\n",
       "      <td>63.7</td>\n",
       "      <td>Customer Visit</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>1151</th>\n",
       "      <td>12/31/2016 13:24</td>\n",
       "      <td>12/31/2016 13:42</td>\n",
       "      <td>Business</td>\n",
       "      <td>Kar?chi</td>\n",
       "      <td>Unknown Location</td>\n",
       "      <td>3.9</td>\n",
       "      <td>Temporary Site</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152</th>\n",
       "      <td>12/31/2016 15:03</td>\n",
       "      <td>12/31/2016 15:38</td>\n",
       "      <td>Business</td>\n",
       "      <td>Unknown Location</td>\n",
       "      <td>Unknown Location</td>\n",
       "      <td>16.2</td>\n",
       "      <td>Meeting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1153</th>\n",
       "      <td>12/31/2016 21:32</td>\n",
       "      <td>12/31/2016 21:50</td>\n",
       "      <td>Business</td>\n",
       "      <td>Katunayake</td>\n",
       "      <td>Gampaha</td>\n",
       "      <td>6.4</td>\n",
       "      <td>Temporary Site</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1154</th>\n",
       "      <td>12/31/2016 22:08</td>\n",
       "      <td>12/31/2016 23:51</td>\n",
       "      <td>Business</td>\n",
       "      <td>Gampaha</td>\n",
       "      <td>Ilukwatta</td>\n",
       "      <td>48.2</td>\n",
       "      <td>Temporary Site</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1155</th>\n",
       "      <td>Totals</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12204.7</td>\n",
       "      <td>NaN</td>\n",
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       "<p>1156 rows × 7 columns</p>\n",
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       "            START_DATE          END_DATE  CATEGORY             START  \\\n",
       "0     01-01-2016 21:11  01-01-2016 21:17  Business       Fort Pierce   \n",
       "1     01-02-2016 01:25  01-02-2016 01:37  Business       Fort Pierce   \n",
       "2     01-02-2016 20:25  01-02-2016 20:38  Business       Fort Pierce   \n",
       "3     01-05-2016 17:31  01-05-2016 17:45  Business       Fort Pierce   \n",
       "4     01-06-2016 14:42  01-06-2016 15:49  Business       Fort Pierce   \n",
       "...                ...               ...       ...               ...   \n",
       "1151  12/31/2016 13:24  12/31/2016 13:42  Business           Kar?chi   \n",
       "1152  12/31/2016 15:03  12/31/2016 15:38  Business  Unknown Location   \n",
       "1153  12/31/2016 21:32  12/31/2016 21:50  Business        Katunayake   \n",
       "1154  12/31/2016 22:08  12/31/2016 23:51  Business           Gampaha   \n",
       "1155            Totals               NaN       NaN               NaN   \n",
       "\n",
       "                  STOP    MILES          PURPOSE  \n",
       "0          Fort Pierce      5.1   Meal/Entertain  \n",
       "1          Fort Pierce      5.0              NaN  \n",
       "2          Fort Pierce      4.8  Errand/Supplies  \n",
       "3          Fort Pierce      4.7          Meeting  \n",
       "4      West Palm Beach     63.7   Customer Visit  \n",
       "...                ...      ...              ...  \n",
       "1151  Unknown Location      3.9   Temporary Site  \n",
       "1152  Unknown Location     16.2          Meeting  \n",
       "1153           Gampaha      6.4   Temporary Site  \n",
       "1154         Ilukwatta     48.2   Temporary Site  \n",
       "1155               NaN  12204.7              NaN  \n",
       "\n",
       "[1156 rows x 7 columns]"
      ]
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   ],
   "source": [
    "# Defining dataframe\n",
    "df = pd.read_csv(\"UberDataset.csv\")\n",
    "\n",
    "# Oversee the data\n",
    "df"
   ]
  },
  {
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   "source": [
    "Apparently, we have an unnecessary record in the index 1155. Thus we are going to drop them."
   ]
  },
  {
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   "source": [
    "# Droping record with index 1155\n",
    "df.drop(index=1155, axis=0, inplace=True)"
   ]
  },
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>START_DATE</th>\n",
       "      <th>END_DATE</th>\n",
       "      <th>CATEGORY</th>\n",
       "      <th>START</th>\n",
       "      <th>STOP</th>\n",
       "      <th>MILES</th>\n",
       "      <th>PURPOSE</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1150</th>\n",
       "      <td>12/31/2016 1:07</td>\n",
       "      <td>12/31/2016 1:14</td>\n",
       "      <td>Business</td>\n",
       "      <td>Kar?chi</td>\n",
       "      <td>Kar?chi</td>\n",
       "      <td>0.7</td>\n",
       "      <td>Meeting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1151</th>\n",
       "      <td>12/31/2016 13:24</td>\n",
       "      <td>12/31/2016 13:42</td>\n",
       "      <td>Business</td>\n",
       "      <td>Kar?chi</td>\n",
       "      <td>Unknown Location</td>\n",
       "      <td>3.9</td>\n",
       "      <td>Temporary Site</td>\n",
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       "    <tr>\n",
       "      <th>1152</th>\n",
       "      <td>12/31/2016 15:03</td>\n",
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       "      <td>Business</td>\n",
       "      <td>Unknown Location</td>\n",
       "      <td>Unknown Location</td>\n",
       "      <td>16.2</td>\n",
       "      <td>Meeting</td>\n",
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       "      <th>1153</th>\n",
       "      <td>12/31/2016 21:32</td>\n",
       "      <td>12/31/2016 21:50</td>\n",
       "      <td>Business</td>\n",
       "      <td>Katunayake</td>\n",
       "      <td>Gampaha</td>\n",
       "      <td>6.4</td>\n",
       "      <td>Temporary Site</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1154</th>\n",
       "      <td>12/31/2016 22:08</td>\n",
       "      <td>12/31/2016 23:51</td>\n",
       "      <td>Business</td>\n",
       "      <td>Gampaha</td>\n",
       "      <td>Ilukwatta</td>\n",
       "      <td>48.2</td>\n",
       "      <td>Temporary Site</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            START_DATE          END_DATE  CATEGORY             START  \\\n",
       "1150   12/31/2016 1:07   12/31/2016 1:14  Business           Kar?chi   \n",
       "1151  12/31/2016 13:24  12/31/2016 13:42  Business           Kar?chi   \n",
       "1152  12/31/2016 15:03  12/31/2016 15:38  Business  Unknown Location   \n",
       "1153  12/31/2016 21:32  12/31/2016 21:50  Business        Katunayake   \n",
       "1154  12/31/2016 22:08  12/31/2016 23:51  Business           Gampaha   \n",
       "\n",
       "                  STOP  MILES         PURPOSE  \n",
       "1150           Kar?chi    0.7         Meeting  \n",
       "1151  Unknown Location    3.9  Temporary Site  \n",
       "1152  Unknown Location   16.2         Meeting  \n",
       "1153           Gampaha    6.4  Temporary Site  \n",
       "1154         Ilukwatta   48.2  Temporary Site  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking data\n",
    "df.tail()"
   ]
  },
  {
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   "id": "226896a2",
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "START_DATE     object\n",
       "END_DATE       object\n",
       "CATEGORY       object\n",
       "START          object\n",
       "STOP           object\n",
       "MILES         float64\n",
       "PURPOSE        object\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking datatypes\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4084ac8",
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    "tags": []
   },
   "source": [
    "- We have the `START_DATE` and the `END_DATE` column in our data that consists of the date and timestamp of each Uber trip.\n",
    "- These columns are still having `object` datatypes.\n",
    "- To ease our analysis, we are going to change their data types from object to datetime."
   ]
  },
  {
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    },
    "tags": []
   },
   "source": [
    "## Converting necessary column to datetime object"
   ]
  },
  {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Converting START_DATE datatypes\n",
    "df['START_DATE'] = pd.to_datetime(df['START_DATE'], format='%m/%d/%Y %H:%M', errors='coerce', utc=True)\n",
    "\n",
    "# Converting END_DATE datatypes\n",
    "df['END_DATE'] = pd.to_datetime(df['END_DATE'], format='%m/%d/%Y %H:%M', errors='coerce', utc=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a85b2754",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:28.511886Z",
     "iopub.status.busy": "2023-09-05T11:55:28.511504Z",
     "iopub.status.idle": "2023-09-05T11:55:28.519577Z",
     "shell.execute_reply": "2023-09-05T11:55:28.518269Z"
    },
    "papermill": {
     "duration": 0.038991,
     "end_time": "2023-09-05T11:55:28.522143",
     "exception": false,
     "start_time": "2023-09-05T11:55:28.483152",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "START_DATE    datetime64[ns, UTC]\n",
       "END_DATE      datetime64[ns, UTC]\n",
       "CATEGORY                   object\n",
       "START                      object\n",
       "STOP                       object\n",
       "MILES                     float64\n",
       "PURPOSE                    object\n",
       "dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking changes\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4916f9b4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-07-28T06:17:37.915076Z",
     "iopub.status.busy": "2023-07-28T06:17:37.914392Z",
     "iopub.status.idle": "2023-07-28T06:17:37.927878Z",
     "shell.execute_reply": "2023-07-28T06:17:37.924096Z",
     "shell.execute_reply.started": "2023-07-28T06:17:37.915016Z"
    },
    "papermill": {
     "duration": 0.028702,
     "end_time": "2023-09-05T11:55:28.578149",
     "exception": false,
     "start_time": "2023-09-05T11:55:28.549447",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Okay so now all columns have their data types the way we desired.\n",
    "- However, we are going to rename columns `START` and `STOP` to `START_POINT` and `STOP_POINT` respectively so that it can be more self-explaining."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23f0a3a6",
   "metadata": {
    "papermill": {
     "duration": 0.028511,
     "end_time": "2023-09-05T11:55:28.634454",
     "exception": false,
     "start_time": "2023-09-05T11:55:28.605943",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Renaming columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c56b1a7c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:28.692564Z",
     "iopub.status.busy": "2023-09-05T11:55:28.690936Z",
     "iopub.status.idle": "2023-09-05T11:55:28.700492Z",
     "shell.execute_reply": "2023-09-05T11:55:28.699420Z"
    },
    "papermill": {
     "duration": 0.040965,
     "end_time": "2023-09-05T11:55:28.702968",
     "exception": false,
     "start_time": "2023-09-05T11:55:28.662003",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Renaming columns\n",
    "df.rename(columns={'START': 'START_POINT', 'STOP': 'STOP_POINT'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "29054666",
   "metadata": {
    "_kg_hide-output": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:28.761119Z",
     "iopub.status.busy": "2023-09-05T11:55:28.760053Z",
     "iopub.status.idle": "2023-09-05T11:55:28.787929Z",
     "shell.execute_reply": "2023-09-05T11:55:28.785443Z"
    },
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     "duration": 0.06105,
     "end_time": "2023-09-05T11:55:28.792184",
     "exception": false,
     "start_time": "2023-09-05T11:55:28.731134",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>START_DATE</th>\n",
       "      <th>END_DATE</th>\n",
       "      <th>CATEGORY</th>\n",
       "      <th>START_POINT</th>\n",
       "      <th>STOP_POINT</th>\n",
       "      <th>MILES</th>\n",
       "      <th>PURPOSE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>Business</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>5.1</td>\n",
       "      <td>Meal/Entertain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>Business</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>Business</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>4.8</td>\n",
       "      <td>Errand/Supplies</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>Business</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>4.7</td>\n",
       "      <td>Meeting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>Business</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>West Palm Beach</td>\n",
       "      <td>63.7</td>\n",
       "      <td>Customer Visit</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1150</th>\n",
       "      <td>2016-12-31 01:07:00+00:00</td>\n",
       "      <td>2016-12-31 01:14:00+00:00</td>\n",
       "      <td>Business</td>\n",
       "      <td>Kar?chi</td>\n",
       "      <td>Kar?chi</td>\n",
       "      <td>0.7</td>\n",
       "      <td>Meeting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1151</th>\n",
       "      <td>2016-12-31 13:24:00+00:00</td>\n",
       "      <td>2016-12-31 13:42:00+00:00</td>\n",
       "      <td>Business</td>\n",
       "      <td>Kar?chi</td>\n",
       "      <td>Unknown Location</td>\n",
       "      <td>3.9</td>\n",
       "      <td>Temporary Site</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152</th>\n",
       "      <td>2016-12-31 15:03:00+00:00</td>\n",
       "      <td>2016-12-31 15:38:00+00:00</td>\n",
       "      <td>Business</td>\n",
       "      <td>Unknown Location</td>\n",
       "      <td>Unknown Location</td>\n",
       "      <td>16.2</td>\n",
       "      <td>Meeting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1153</th>\n",
       "      <td>2016-12-31 21:32:00+00:00</td>\n",
       "      <td>2016-12-31 21:50:00+00:00</td>\n",
       "      <td>Business</td>\n",
       "      <td>Katunayake</td>\n",
       "      <td>Gampaha</td>\n",
       "      <td>6.4</td>\n",
       "      <td>Temporary Site</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1154</th>\n",
       "      <td>2016-12-31 22:08:00+00:00</td>\n",
       "      <td>2016-12-31 23:51:00+00:00</td>\n",
       "      <td>Business</td>\n",
       "      <td>Gampaha</td>\n",
       "      <td>Ilukwatta</td>\n",
       "      <td>48.2</td>\n",
       "      <td>Temporary Site</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1155 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    START_DATE                  END_DATE  CATEGORY  \\\n",
       "0                          NaT                       NaT  Business   \n",
       "1                          NaT                       NaT  Business   \n",
       "2                          NaT                       NaT  Business   \n",
       "3                          NaT                       NaT  Business   \n",
       "4                          NaT                       NaT  Business   \n",
       "...                        ...                       ...       ...   \n",
       "1150 2016-12-31 01:07:00+00:00 2016-12-31 01:14:00+00:00  Business   \n",
       "1151 2016-12-31 13:24:00+00:00 2016-12-31 13:42:00+00:00  Business   \n",
       "1152 2016-12-31 15:03:00+00:00 2016-12-31 15:38:00+00:00  Business   \n",
       "1153 2016-12-31 21:32:00+00:00 2016-12-31 21:50:00+00:00  Business   \n",
       "1154 2016-12-31 22:08:00+00:00 2016-12-31 23:51:00+00:00  Business   \n",
       "\n",
       "           START_POINT        STOP_POINT  MILES          PURPOSE  \n",
       "0          Fort Pierce       Fort Pierce    5.1   Meal/Entertain  \n",
       "1          Fort Pierce       Fort Pierce    5.0              NaN  \n",
       "2          Fort Pierce       Fort Pierce    4.8  Errand/Supplies  \n",
       "3          Fort Pierce       Fort Pierce    4.7          Meeting  \n",
       "4          Fort Pierce   West Palm Beach   63.7   Customer Visit  \n",
       "...                ...               ...    ...              ...  \n",
       "1150           Kar?chi           Kar?chi    0.7          Meeting  \n",
       "1151           Kar?chi  Unknown Location    3.9   Temporary Site  \n",
       "1152  Unknown Location  Unknown Location   16.2          Meeting  \n",
       "1153        Katunayake           Gampaha    6.4   Temporary Site  \n",
       "1154           Gampaha         Ilukwatta   48.2   Temporary Site  \n",
       "\n",
       "[1155 rows x 7 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking dataframe\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28d3174f",
   "metadata": {
    "papermill": {
     "duration": 0.035786,
     "end_time": "2023-09-05T11:55:28.865025",
     "exception": false,
     "start_time": "2023-09-05T11:55:28.829239",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Cleaning the data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6d129f6",
   "metadata": {
    "papermill": {
     "duration": 0.038072,
     "end_time": "2023-09-05T11:55:28.941711",
     "exception": false,
     "start_time": "2023-09-05T11:55:28.903639",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Checking duplicated values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad273305",
   "metadata": {
    "papermill": {
     "duration": 0.038979,
     "end_time": "2023-09-05T11:55:29.019477",
     "exception": false,
     "start_time": "2023-09-05T11:55:28.980498",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Creating function to check and remove duplicates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "acfe38d7",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:29.083133Z",
     "iopub.status.busy": "2023-09-05T11:55:29.081926Z",
     "iopub.status.idle": "2023-09-05T11:55:29.091832Z",
     "shell.execute_reply": "2023-09-05T11:55:29.090229Z"
    },
    "papermill": {
     "duration": 0.042901,
     "end_time": "2023-09-05T11:55:29.094811",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.051910",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Creating function to check and remove duplicates\n",
    "def duplicateVal(df):\n",
    "    # Checking shape before dropping duplicates\n",
    "    before_drop = df.shape\n",
    "    print(f'shape before dropping duplicate: {before_drop}')\n",
    "\n",
    "    # Calculating total duplicated data\n",
    "    total_duplicate = df.duplicated().sum()\n",
    "    print(f'Total duplicated records: {total_duplicate}')\n",
    "\n",
    "    # Dropping duplicated data\n",
    "    df = df.drop_duplicates()\n",
    "\n",
    "    # Checking shape after dropping duplicates\n",
    "    after_drop = df.shape\n",
    "    print(f'shape before dropping duplicate: {after_drop}')\n",
    "    \n",
    "    # Returning dataframe after droping duplicate\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ac25e06c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:29.154686Z",
     "iopub.status.busy": "2023-09-05T11:55:29.153538Z",
     "iopub.status.idle": "2023-09-05T11:55:29.171932Z",
     "shell.execute_reply": "2023-09-05T11:55:29.170766Z"
    },
    "papermill": {
     "duration": 0.051058,
     "end_time": "2023-09-05T11:55:29.174604",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.123546",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape before dropping duplicate: (1155, 7)\n",
      "Total duplicated records: 43\n",
      "shape before dropping duplicate: (1112, 7)\n"
     ]
    }
   ],
   "source": [
    "df = duplicateVal(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db50023c",
   "metadata": {
    "papermill": {
     "duration": 0.027915,
     "end_time": "2023-09-05T11:55:29.236344",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.208429",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Okay we have dropped the duplicated values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a38e141",
   "metadata": {
    "papermill": {
     "duration": 0.032035,
     "end_time": "2023-09-05T11:55:29.295647",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.263612",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Checking missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e7e7ef65",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:29.357655Z",
     "iopub.status.busy": "2023-09-05T11:55:29.356502Z",
     "iopub.status.idle": "2023-09-05T11:55:29.364783Z",
     "shell.execute_reply": "2023-09-05T11:55:29.363543Z"
    },
    "papermill": {
     "duration": 0.044476,
     "end_time": "2023-09-05T11:55:29.370444",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.325968",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Creating function to check null values\n",
    "def missVal(data):\n",
    "    # Calculating total missing values in each column\n",
    "    total = data.isna().sum().sort_values(ascending=False)\n",
    "    \n",
    "    # Calculating missing value percentage in each column\n",
    "    percent = total/len(data)\n",
    "    \n",
    "    # Returning result\n",
    "    return pd.concat([total, percent], keys=['Total', 'Missing Persentage'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0c1a900a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:29.427180Z",
     "iopub.status.busy": "2023-09-05T11:55:29.426726Z",
     "iopub.status.idle": "2023-09-05T11:55:29.444943Z",
     "shell.execute_reply": "2023-09-05T11:55:29.443569Z"
    },
    "papermill": {
     "duration": 0.050098,
     "end_time": "2023-09-05T11:55:29.448022",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.397924",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\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>Total</th>\n",
       "      <th>Missing Persentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PURPOSE</th>\n",
       "      <td>499</td>\n",
       "      <td>0.448741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>START_DATE</th>\n",
       "      <td>379</td>\n",
       "      <td>0.340827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>END_DATE</th>\n",
       "      <td>378</td>\n",
       "      <td>0.339928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CATEGORY</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>START_POINT</th>\n",
       "      <td>0</td>\n",
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       "      <th>STOP_POINT</th>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>MILES</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
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       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "             Total  Missing Persentage\n",
       "PURPOSE        499            0.448741\n",
       "START_DATE     379            0.340827\n",
       "END_DATE       378            0.339928\n",
       "CATEGORY         0            0.000000\n",
       "START_POINT      0            0.000000\n",
       "STOP_POINT       0            0.000000\n",
       "MILES            0            0.000000"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking null values\n",
    "missVal(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efcbe2f1",
   "metadata": {
    "papermill": {
     "duration": 0.027554,
     "end_time": "2023-09-05T11:55:29.503346",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.475792",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Okay so we only have 1 column that has missing values and that is the `PURPOSE` column which has a total of 502 missing values or there are ~43% data missing.\n",
    "- Let's zoom in on the `PURPOSE` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ee12d1a8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:29.562343Z",
     "iopub.status.busy": "2023-09-05T11:55:29.561251Z",
     "iopub.status.idle": "2023-09-05T11:55:29.575610Z",
     "shell.execute_reply": "2023-09-05T11:55:29.574167Z"
    },
    "papermill": {
     "duration": 0.046604,
     "end_time": "2023-09-05T11:55:29.578191",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.531587",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Meeting            164\n",
       "Meal/Entertain     152\n",
       "Errand/Supplies    125\n",
       "Customer Visit      96\n",
       "Temporary Site      49\n",
       "Between Offices     18\n",
       "Moving               4\n",
       "Airport/Travel       3\n",
       "Charity ($)          1\n",
       "Commute              1\n",
       "Name: PURPOSE, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking unique values in column PURPOSE\n",
    "df['PURPOSE'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e600daf3",
   "metadata": {
    "papermill": {
     "duration": 0.030908,
     "end_time": "2023-09-05T11:55:29.637016",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.606108",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- It looks like the `PURPOSE` column is just the detail or the note associated with the `CATEGORY` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "99f029ed",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:29.695309Z",
     "iopub.status.busy": "2023-09-05T11:55:29.694365Z",
     "iopub.status.idle": "2023-09-05T11:55:29.705896Z",
     "shell.execute_reply": "2023-09-05T11:55:29.704355Z"
    },
    "papermill": {
     "duration": 0.043554,
     "end_time": "2023-09-05T11:55:29.708426",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.664872",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Business    1035\n",
      "Personal      77\n",
      "Name: CATEGORY, dtype: int64\n",
      "\n",
      "Meeting            164\n",
      "Meal/Entertain     152\n",
      "Errand/Supplies    125\n",
      "Customer Visit      96\n",
      "Temporary Site      49\n",
      "Between Offices     18\n",
      "Moving               4\n",
      "Airport/Travel       3\n",
      "Charity ($)          1\n",
      "Commute              1\n",
      "Name: PURPOSE, dtype: int64\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Checking PURPOSE and CATEGORY columns unique values individually\n",
    "to_check = ['CATEGORY', 'PURPOSE']\n",
    "for col in to_check:\n",
    "    print(df[col].value_counts())\n",
    "    print('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "dc1d7a5d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:29.767035Z",
     "iopub.status.busy": "2023-09-05T11:55:29.766647Z",
     "iopub.status.idle": "2023-09-05T11:55:29.783657Z",
     "shell.execute_reply": "2023-09-05T11:55:29.782564Z"
    },
    "papermill": {
     "duration": 0.049068,
     "end_time": "2023-09-05T11:55:29.785862",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.736794",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CATEGORY  PURPOSE        \n",
       "Business  Airport/Travel       3\n",
       "          Between Offices     18\n",
       "          Customer Visit      96\n",
       "          Errand/Supplies    125\n",
       "          Meal/Entertain     152\n",
       "          Meeting            164\n",
       "          Temporary Site      49\n",
       "Personal  Charity ($)          1\n",
       "          Commute              1\n",
       "          Moving               4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking PURPOSE and CATEGORY columns combined unique values\n",
    "df[['CATEGORY', 'PURPOSE']].value_counts().sort_index(level=0, ascending=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47700b6e",
   "metadata": {
    "papermill": {
     "duration": 0.027615,
     "end_time": "2023-09-05T11:55:29.841793",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.814178",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Actually, we can fill in the missing values in the `PURPOSE` column later by looking at some pattern in each `PURPOSE` category.\n",
    "- Or, other best practices suggest that missing values can be filled with 'UNKNOWN' value.\n",
    "- We also get additional information that `PURPOSE` column has rare values like `Charity`, `Commute`, `Moving`, `Airport/Travel`, and `Between Offices`\n",
    "- In the context of preparing data for machine learning, we have to do something with these rare values, as it can cause troubles and worsen the model performance in the future.\n",
    "- However, as my purpose for this session is to analyze and visualize the data, I will not take action on the missing values and the rare values."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a46b7ff1",
   "metadata": {
    "papermill": {
     "duration": 0.027699,
     "end_time": "2023-09-05T11:55:29.897365",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.869666",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Checking inconsistent data input (Categorical data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "64a00423",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:29.956019Z",
     "iopub.status.busy": "2023-09-05T11:55:29.954853Z",
     "iopub.status.idle": "2023-09-05T11:55:29.964109Z",
     "shell.execute_reply": "2023-09-05T11:55:29.962756Z"
    },
    "papermill": {
     "duration": 0.042071,
     "end_time": "2023-09-05T11:55:29.967681",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.925610",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "START_DATE     datetime64[ns, UTC]\n",
       "END_DATE       datetime64[ns, UTC]\n",
       "CATEGORY                    object\n",
       "START_POINT                 object\n",
       "STOP_POINT                  object\n",
       "MILES                      float64\n",
       "PURPOSE                     object\n",
       "dtype: object"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking data types\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9b6963fe",
   "metadata": {
    "_kg_hide-input": false,
    "_kg_hide-output": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:30.028175Z",
     "iopub.status.busy": "2023-09-05T11:55:30.027749Z",
     "iopub.status.idle": "2023-09-05T11:55:30.042621Z",
     "shell.execute_reply": "2023-09-05T11:55:30.041034Z"
    },
    "papermill": {
     "duration": 0.047758,
     "end_time": "2023-09-05T11:55:30.045074",
     "exception": false,
     "start_time": "2023-09-05T11:55:29.997316",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Business    1035\n",
      "Personal      77\n",
      "Name: CATEGORY, dtype: int64\n",
      "\n",
      "Cary                181\n",
      "Unknown Location    148\n",
      "Morrisville          78\n",
      "Whitebridge          66\n",
      "Islamabad            57\n",
      "                   ... \n",
      "Florence              1\n",
      "Ridgeland             1\n",
      "Daytona Beach         1\n",
      "Sky Lake              1\n",
      "Gampaha               1\n",
      "Name: START_POINT, Length: 177, dtype: int64\n",
      "\n",
      "Cary                 183\n",
      "Unknown Location     149\n",
      "Morrisville           76\n",
      "Whitebridge           62\n",
      "Islamabad             58\n",
      "                    ... \n",
      "Daytona Beach          1\n",
      "Sand Lake Commons      1\n",
      "Sky Lake               1\n",
      "Vista East             1\n",
      "Ilukwatta              1\n",
      "Name: STOP_POINT, Length: 188, dtype: int64\n",
      "\n",
      "Meeting            164\n",
      "Meal/Entertain     152\n",
      "Errand/Supplies    125\n",
      "Customer Visit      96\n",
      "Temporary Site      49\n",
      "Between Offices     18\n",
      "Moving               4\n",
      "Airport/Travel       3\n",
      "Charity ($)          1\n",
      "Commute              1\n",
      "Name: PURPOSE, dtype: int64\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Checking categorical/str data unique values\n",
    "for col in df.columns:\n",
    "    if df[col].dtypes == object:\n",
    "        print(df[col].value_counts())\n",
    "        print('')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d6cd0e8",
   "metadata": {
    "papermill": {
     "duration": 0.028236,
     "end_time": "2023-09-05T11:55:30.102169",
     "exception": false,
     "start_time": "2023-09-05T11:55:30.073933",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- As we can see from the previous code and the code above, the `CATEGORY` and the `PURPOSE` columns already have consistent data input.\n",
    "- However, we have to see the details of how the data in the `START_POINT` and `STOP_POINT` columns are inputted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fd52845a",
   "metadata": {
    "_kg_hide-output": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:30.162652Z",
     "iopub.status.busy": "2023-09-05T11:55:30.162173Z",
     "iopub.status.idle": "2023-09-05T11:55:30.171739Z",
     "shell.execute_reply": "2023-09-05T11:55:30.170637Z"
    },
    "papermill": {
     "duration": 0.043516,
     "end_time": "2023-09-05T11:55:30.174760",
     "exception": false,
     "start_time": "2023-09-05T11:55:30.131244",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Agnew\n",
      "Almond\n",
      "Apex\n",
      "Arabi\n",
      "Arlington\n",
      "Arlington Park at Amberly\n",
      "Asheville\n",
      "Austin\n",
      "Banner Elk\n",
      "Bellevue\n",
      "Berkeley\n",
      "Boone\n",
      "Briar Meadow\n",
      "Bryson City\n",
      "Burtrose\n",
      "CBD\n",
      "Capitol One\n",
      "Cary\n",
      "Central\n",
      "Chalmette\n",
      "Chapel Hill\n",
      "Chessington\n",
      "College Avenue\n",
      "Colombo\n",
      "Columbia Heights\n",
      "Congress Ave District\n",
      "Connecticut Avenue\n",
      "Convention Center District\n",
      "Cory\n",
      "Couples Glen\n",
      "Covington\n",
      "Coxville\n",
      "Daytona Beach\n",
      "Downtown\n",
      "Durham\n",
      "Eagan Park\n",
      "Eagle Rock\n",
      "East Austin\n",
      "East Elmhurst\n",
      "East Harlem\n",
      "Eastgate\n",
      "Edgehill Farms\n",
      "El Cerrito\n",
      "Elk Park\n",
      "Elmhurst\n",
      "Emeryville\n",
      "Fairmont\n",
      "Farmington Woods\n",
      "Fayetteville Street\n",
      "Financial District\n",
      "Flatiron District\n",
      "Florence\n",
      "Fort Pierce\n",
      "Fuquay-Varina\n",
      "Galveston\n",
      "Gampaha\n",
      "Georgian Acres\n",
      "Gulfton\n",
      "Hayesville\n",
      "Hazelwood\n",
      "Hell's Kitchen\n",
      "Heritage Pines\n",
      "Holly Springs\n",
      "Houston\n",
      "Hudson Square\n",
      "Huntington Woods\n",
      "Ingleside\n",
      "Islamabad\n",
      "Jackson Heights\n",
      "Jacksonville\n",
      "Jamaica\n",
      "Jamestown Court\n",
      "K Street\n",
      "Kalorama Triangle\n",
      "Kar?chi\n",
      "Karachi\n",
      "Katunayaka\n",
      "Katunayake\n",
      "Katy\n",
      "Kenner\n",
      "Kilarney Woods\n",
      "Kissimmee\n",
      "Krendle Woods\n",
      "Lahore\n",
      "Lake Reams\n",
      "Lake Wellingborough\n",
      "Lakeview\n",
      "Latta\n",
      "Lexington Park at Amberly\n",
      "Long Island City\n",
      "Lower Garden District\n",
      "Lower Manhattan\n",
      "Mandeville\n",
      "Marigny\n",
      "Mcvan\n",
      "Mebane\n",
      "Medical Centre\n",
      "Menlo Park\n",
      "Meredith\n",
      "Meredith Townes\n",
      "Metairie\n",
      "Midtown\n",
      "Midtown East\n",
      "Morrisville\n",
      "Mountain View\n",
      "NOMA\n",
      "New Orleans\n",
      "New York\n",
      "Newark\n",
      "Newland\n",
      "Noorpur Shahan\n",
      "North Austin\n",
      "North Berkeley Hills\n",
      "Northwoods\n",
      "Nugegoda\n",
      "Oakland\n",
      "Old City\n",
      "Orlando\n",
      "Palo Alto\n",
      "Parkway\n",
      "Parkwood\n",
      "Pontchartrain Beach\n",
      "Pontchartrain Shores\n",
      "Port Bolivar\n",
      "Preston\n",
      "R?walpindi\n",
      "Raleigh\n",
      "Rawalpindi\n",
      "Red River District\n",
      "Redmond\n",
      "Renaissance\n",
      "Ridgeland\n",
      "Rose Hill\n",
      "SOMISSPO\n",
      "San Francisco\n",
      "San Jose\n",
      "Sand Lake Commons\n",
      "Santa Clara\n",
      "Savon Height\n",
      "Seaport\n",
      "Seattle\n",
      "Sharpstown\n",
      "Sky Lake\n",
      "Soho\n",
      "South\n",
      "South Berkeley\n",
      "South Congress\n",
      "Southside\n",
      "St Thomas\n",
      "Stonewater\n",
      "Storyville\n",
      "Sugar Land\n",
      "Summerwinds\n",
      "Sunnyside\n",
      "Sunnyvale\n",
      "Tanglewood\n",
      "Tenderloin\n",
      "The Drag\n",
      "Topton\n",
      "Townes at Everett Crossing\n",
      "Tribeca\n",
      "University District\n",
      "Unknown Location\n",
      "Wake Co.\n",
      "Wake Forest\n",
      "Washington\n",
      "Washington Avenue\n",
      "Waverly Place\n",
      "Wayne Ridge\n",
      "West Berkeley\n",
      "West End\n",
      "West Palm Beach\n",
      "West University\n",
      "Weston\n",
      "Westpark Place\n",
      "Whitebridge\n",
      "Winston Salem\n"
     ]
    }
   ],
   "source": [
    "for i in df['START_POINT'].value_counts().sort_index().index:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2e43b80",
   "metadata": {
    "papermill": {
     "duration": 0.028467,
     "end_time": "2023-09-05T11:55:30.231930",
     "exception": false,
     "start_time": "2023-09-05T11:55:30.203463",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "In the **START_POINT** column, the values below are inconsistent. They are supposed to be one value because they refer to the same location.\n",
    "\n",
    "- Kar?chi and Karachi are supposed to be **Karachi** (a city in Pakistan)\n",
    "- Katunayaka and Katunayake supposed to be **Katunayake** (International airport in Sri Lanka)\n",
    "- Pontchartrain Beach and Pontchartrain Shores refer to a highly close location and therefore can be merged into one value, and that is **Pontchartrain Beach** (an amusement park in the U.S.)\n",
    "- R?walpindi and **Rawalpindi** are supposed to be Rawalpindi (a city in Pakistan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "84322ca0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:30.292419Z",
     "iopub.status.busy": "2023-09-05T11:55:30.291347Z",
     "iopub.status.idle": "2023-09-05T11:55:30.300888Z",
     "shell.execute_reply": "2023-09-05T11:55:30.300082Z"
    },
    "papermill": {
     "duration": 0.042312,
     "end_time": "2023-09-05T11:55:30.303033",
     "exception": false,
     "start_time": "2023-09-05T11:55:30.260721",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Kar?chi                 27\n",
       "R?walpindi              11\n",
       "Katunayaka               2\n",
       "Pontchartrain Shores     2\n",
       "Name: START_POINT, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's see how much of this inconsistent data\n",
    "incons_data = ['Kar?chi', 'Katunayaka', 'Pontchartrain Shores', 'R?walpindi']\n",
    "df.loc[df['START_POINT'].isin(incons_data), 'START_POINT'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "895ac8ce",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:30.362813Z",
     "iopub.status.busy": "2023-09-05T11:55:30.362152Z",
     "iopub.status.idle": "2023-09-05T11:55:30.370825Z",
     "shell.execute_reply": "2023-09-05T11:55:30.369079Z"
    },
    "papermill": {
     "duration": 0.042031,
     "end_time": "2023-09-05T11:55:30.373944",
     "exception": false,
     "start_time": "2023-09-05T11:55:30.331913",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\HP\\AppData\\Local\\Temp\\ipykernel_12952\\509483552.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['START_POINT'].replace({\n"
     ]
    }
   ],
   "source": [
    "# Consistening values in the START_POINT column\n",
    "df['START_POINT'].replace({\n",
    "    'Kar?chi': 'Karachi',\n",
    "    'Katunayaka': 'Katunayake',\n",
    "    'Pontchartrain Shores': 'Pontchartrain Beach',\n",
    "    'R?walpindi': 'Rawalpindi'\n",
    "}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "cbf8eaab",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:30.434396Z",
     "iopub.status.busy": "2023-09-05T11:55:30.433281Z",
     "iopub.status.idle": "2023-09-05T11:55:30.441069Z",
     "shell.execute_reply": "2023-09-05T11:55:30.440252Z"
    },
    "papermill": {
     "duration": 0.040417,
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     "exception": false,
     "start_time": "2023-09-05T11:55:30.403010",
     "status": "completed"
    },
    "tags": []
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking data\n",
    "df['START_POINT'].isin(incons_data).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a36d8d8e",
   "metadata": {
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    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Agnew\n",
      "Alief\n",
      "Almond\n",
      "Apex\n",
      "Arabi\n",
      "Arlington\n",
      "Arlington Park at Amberly\n",
      "Arts District\n",
      "Asheville\n",
      "Banner Elk\n",
      "Bay Farm Island\n",
      "Bellevue\n",
      "Berkeley\n",
      "Boone\n",
      "Briar Meadow\n",
      "Bryson City\n",
      "Burtrose\n",
      "Bywater\n",
      "CBD\n",
      "Capitol One\n",
      "Cary\n",
      "Cedar Hill\n",
      "Central\n",
      "Chalmette\n",
      "Chapel Hill\n",
      "Chessington\n",
      "College Avenue\n",
      "Colombo\n",
      "Columbia Heights\n",
      "Congress Ave District\n",
      "Convention Center District\n",
      "Cory\n",
      "Covington\n",
      "Coxville\n",
      "Daytona Beach\n",
      "Depot Historic District\n",
      "Downtown\n",
      "Durham\n",
      "Eagle Rock\n",
      "East Elmhurst\n",
      "East Harlem\n",
      "Edgehill Farms\n",
      "El Cerrito\n",
      "Elk Park\n",
      "Emeryville\n",
      "Farmington Woods\n",
      "Faubourg Marigny\n",
      "Financial District\n",
      "Florence\n",
      "Fort Pierce\n",
      "French Quarter\n",
      "Fuquay-Varina\n",
      "Galveston\n",
      "Gampaha\n",
      "Gramercy-Flatiron\n",
      "Greater Greenspoint\n",
      "Gulfton\n",
      "Harden Place\n",
      "Hayesville\n",
      "Hazelwood\n",
      "Hell's Kitchen\n",
      "Heritage Pines\n",
      "Hog Island\n",
      "Holly Springs\n",
      "Houston\n",
      "Hudson Square\n",
      "Huntington Woods\n",
      "Ilukwatta\n",
      "Ingleside\n",
      "Islamabad\n",
      "Isles of Buena Vista\n",
      "Jackson Heights\n",
      "Jacksonville\n",
      "Jamaica\n",
      "Jamestown Court\n",
      "K Street\n",
      "Kalorama Triangle\n",
      "Kar?chi\n",
      "Karachi\n",
      "Katunayaka\n",
      "Katy\n",
      "Kenner\n",
      "Kilarney Woods\n",
      "Kildaire Farms\n",
      "Kips Bay\n",
      "Kissimmee\n",
      "Lahore\n",
      "Lake Reams\n",
      "Lake Wellingborough\n",
      "Lakeview\n",
      "Latta\n",
      "Leesville Hollow\n",
      "Lexington Park at Amberly\n",
      "Long Island City\n",
      "Lower Garden District\n",
      "Lower Manhattan\n",
      "Macgregor Downs\n",
      "Mandeville\n",
      "Marigny\n",
      "Mcvan\n",
      "Mebane\n",
      "Menlo Park\n",
      "Meredith Townes\n",
      "Metairie\n",
      "Midtown\n",
      "Midtown East\n",
      "Midtown West\n",
      "Morrisville\n",
      "Mountain View\n",
      "New Orleans\n",
      "New York\n",
      "Newark\n",
      "Newland\n",
      "NoMad\n",
      "Noorpur Shahan\n",
      "North Austin\n",
      "North Berkeley Hills\n",
      "Northwest Rectangle\n",
      "Northwoods\n",
      "Nugegoda\n",
      "Oakland\n",
      "Orlando\n",
      "Palm Beach\n",
      "Palo Alto\n",
      "Parkway\n",
      "Parkway Museums\n",
      "Parkwood\n",
      "Pontchartrain Beach\n",
      "Pontchartrain Shores\n",
      "Port Bolivar\n",
      "Potrero Flats\n",
      "Preston\n",
      "Queens\n",
      "Queens County\n",
      "R?walpindi\n",
      "Raleigh\n",
      "Rawalpindi\n",
      "Red River District\n",
      "Redmond\n",
      "Renaissance\n",
      "Ridgeland\n",
      "SOMISSPO\n",
      "San Francisco\n",
      "San Jose\n",
      "Sand Lake Commons\n",
      "Santa Clara\n",
      "Savon Height\n",
      "Seattle\n",
      "Sharpstown\n",
      "Sky Lake\n",
      "Soho\n",
      "South\n",
      "South Berkeley\n",
      "South Congress\n",
      "Southside\n",
      "Southwest Berkeley\n",
      "St Thomas\n",
      "Stonewater\n",
      "Storyville\n",
      "Sugar Land\n",
      "Summerwinds\n",
      "Sunnyside\n",
      "Sunnyvale\n",
      "Tanglewood\n",
      "Tenderloin\n",
      "The Drag\n",
      "Topton\n",
      "Tribeca\n",
      "Tudor City\n",
      "Umstead\n",
      "University District\n",
      "Unknown Location\n",
      "Vista East\n",
      "Wake Co.\n",
      "Wake Forest\n",
      "Walnut Terrace\n",
      "Washington\n",
      "Washington Avenue\n",
      "Waverly Place\n",
      "Wayne Ridge\n",
      "West Berkeley\n",
      "West Palm Beach\n",
      "West University\n",
      "Weston\n",
      "Westpark Place\n",
      "Whitebridge\n",
      "Williamsburg Manor\n",
      "Winston Salem\n"
     ]
    }
   ],
   "source": [
    "# Now let's see the data in the STOP_POINT column\n",
    "for i in df['STOP_POINT'].value_counts().sort_index().index:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "504afb8c",
   "metadata": {
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     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "In the **STOP_POINT** column, the values below are inconsistent. They are supposed to be one value because they refer to the same location.\n",
    "\n",
    "- Kar?chi and Karachi are supposed to be **Karachi** (a city in Pakistan)\n",
    "- Katunayaka is supposed to be **Katunayake** (International airport in Sri Lanka)\n",
    "- Pontchartrain Beach and Pontchartrain Shores refer to a highly close location and therefore can be merged into one value, and that is **Pontchartrain Beach** (an amusement park in the U.S.)\n",
    "- R?walpindi and **Rawalpindi** are supposed to be Rawalpindi (a city in Pakistan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "8ee5dca0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:30.635561Z",
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     "shell.execute_reply": "2023-09-05T11:55:30.644939Z"
    },
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Kar?chi                 26\n",
       "R?walpindi              13\n",
       "Katunayaka               2\n",
       "Pontchartrain Shores     2\n",
       "Name: STOP_POINT, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's see how much of this inconsistent data\n",
    "incons_data = ['Kar?chi', 'Katunayaka', 'Pontchartrain Shores', 'R?walpindi']\n",
    "df.loc[df['STOP_POINT'].isin(incons_data), 'STOP_POINT'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "3481d945",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:30.709606Z",
     "iopub.status.busy": "2023-09-05T11:55:30.709127Z",
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     "shell.execute_reply": "2023-09-05T11:55:30.717054Z"
    },
    "papermill": {
     "duration": 0.042916,
     "end_time": "2023-09-05T11:55:30.720885",
     "exception": false,
     "start_time": "2023-09-05T11:55:30.677969",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\HP\\AppData\\Local\\Temp\\ipykernel_12952\\1298918841.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['STOP_POINT'].replace({\n"
     ]
    }
   ],
   "source": [
    "# Consistening values in the STOP_POINT column\n",
    "df['STOP_POINT'].replace({\n",
    "    'Kar?chi': 'Karachi',\n",
    "    'Katunayaka': 'Katunayake',\n",
    "    'Pontchartrain Shores': 'Pontchartrain Beach',\n",
    "    'R?walpindi': 'Rawalpindi'\n",
    "}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "292ec909",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:30.783115Z",
     "iopub.status.busy": "2023-09-05T11:55:30.782589Z",
     "iopub.status.idle": "2023-09-05T11:55:30.792684Z",
     "shell.execute_reply": "2023-09-05T11:55:30.791717Z"
    },
    "papermill": {
     "duration": 0.044341,
     "end_time": "2023-09-05T11:55:30.795109",
     "exception": false,
     "start_time": "2023-09-05T11:55:30.750768",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking data\n",
    "df['STOP_POINT'].isin(incons_data).sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be08621c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-07-28T06:32:29.419585Z",
     "iopub.status.busy": "2023-07-28T06:32:29.419062Z",
     "iopub.status.idle": "2023-07-28T06:32:29.427907Z",
     "shell.execute_reply": "2023-07-28T06:32:29.426160Z",
     "shell.execute_reply.started": "2023-07-28T06:32:29.419548Z"
    },
    "papermill": {
     "duration": 0.029361,
     "end_time": "2023-09-05T11:55:30.854118",
     "exception": false,
     "start_time": "2023-09-05T11:55:30.824757",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Okay, so now all our categorical data are consistent we can examine our numerical data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e45a692",
   "metadata": {
    "papermill": {
     "duration": 0.02912,
     "end_time": "2023-09-05T11:55:30.912683",
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     "start_time": "2023-09-05T11:55:30.883563",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Checking outliers and anomaly (Numerical data)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "1c497b25",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:30.974561Z",
     "iopub.status.busy": "2023-09-05T11:55:30.973796Z",
     "iopub.status.idle": "2023-09-05T11:55:30.983550Z",
     "shell.execute_reply": "2023-09-05T11:55:30.982352Z"
    },
    "papermill": {
     "duration": 0.043579,
     "end_time": "2023-09-05T11:55:30.985916",
     "exception": false,
     "start_time": "2023-09-05T11:55:30.942337",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "START_DATE     datetime64[ns, UTC]\n",
       "END_DATE       datetime64[ns, UTC]\n",
       "CATEGORY                    object\n",
       "START_POINT                 object\n",
       "STOP_POINT                  object\n",
       "MILES                      float64\n",
       "PURPOSE                     object\n",
       "dtype: object"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking data types\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7f9b48b1",
   "metadata": {
    "_kg_hide-input": true,
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     "iopub.execute_input": "2023-09-05T11:55:31.047920Z",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Checking distributions in the MILES column\n",
    "\n",
    "# Calculating MILES median\n",
    "miles_median = df['MILES'].median()\n",
    "\n",
    "# Creating figure an\n",
    "fig, ax = plt.subplots(figsize = (10,6))\n",
    "\n",
    "# Plotting \n",
    "sns.kdeplot(\n",
    "    data = df,\n",
    "    x = 'MILES',\n",
    "    ax = ax\n",
    ")\n",
    "\n",
    "# Setting title\n",
    "ax.set_title('Miles Distribution')\n",
    "\n",
    "# Setting average line\n",
    "ax.axvline(miles_median, linestyle='--', label = 'Median')\n",
    "ax.annotate(f'The median miles is {miles_median}', \n",
    "            xy = (25,0.043),\n",
    "            fontsize = 13\n",
    "           )\n",
    "\n",
    "# Showing legend\n",
    "ax.legend(fontsize='large')\n",
    "\n",
    "# Showing plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "972cee50",
   "metadata": {
    "papermill": {
     "duration": 0.03014,
     "end_time": "2023-09-05T11:55:31.585294",
     "exception": false,
     "start_time": "2023-09-05T11:55:31.555154",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "- Here, we can see that the **trip median for this dataset is 6 miles**.\n",
    "- However, **the distribution is right-skewed**, indicating that our trip dataset has outliers in terms of trip distance.\n",
    "- Let's see the descriptive statistic for the `MILES` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "1bcaedbb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:31.649308Z",
     "iopub.status.busy": "2023-09-05T11:55:31.648884Z",
     "iopub.status.idle": "2023-09-05T11:55:31.660825Z",
     "shell.execute_reply": "2023-09-05T11:55:31.659809Z"
    },
    "papermill": {
     "duration": 0.046944,
     "end_time": "2023-09-05T11:55:31.663348",
     "exception": false,
     "start_time": "2023-09-05T11:55:31.616404",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1112.000000\n",
       "mean       10.712050\n",
       "std        21.968587\n",
       "min         0.500000\n",
       "25%         2.800000\n",
       "50%         5.900000\n",
       "75%        10.600000\n",
       "max       310.300000\n",
       "Name: MILES, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Seeing descriptive statistic for MILES column\n",
    "df['MILES'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b58c683",
   "metadata": {
    "papermill": {
     "duration": 0.030803,
     "end_time": "2023-09-05T11:55:31.724881",
     "exception": false,
     "start_time": "2023-09-05T11:55:31.694078",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "We can see that\n",
    "\n",
    "- The minimum trip distance in our dataset is 0.5 Miles\n",
    "- The furthest trip is 310.3 Miles\n",
    "- The 25th quantile is in 2.9 Miles\n",
    "- The 75th quantile is in 10.4 Miles\n",
    "\n",
    "For the purpose of analysis, I'm not going to remove the outliers for now."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c150d3a7",
   "metadata": {
    "papermill": {
     "duration": 0.03055,
     "end_time": "2023-09-05T11:55:31.787064",
     "exception": false,
     "start_time": "2023-09-05T11:55:31.756514",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# EDA\n",
    "- How many Uber trips occurred during the timestamp in the dataset?\n",
    "- What is the median for daily and monthly total trips?\n",
    "- How is the customer segment proportion?\n",
    "- How is the hourly trend for Uber trips?\n",
    "- How are the conditional probabilities of each segment ordering an Uber for each hour?\n",
    "- What are the favorite pick-up spots for each segment?\n",
    "- How is the daily trend for Uber trips?\n",
    "- How is the monthly trend for Uber trips?\n",
    "- Is there any specific characteristic of each segment based on their travel distance?\n",
    "- Is there any specific characteristic of each segment based on the travel duration?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9387033",
   "metadata": {
    "papermill": {
     "duration": 0.030297,
     "end_time": "2023-09-05T11:55:31.847952",
     "exception": false,
     "start_time": "2023-09-05T11:55:31.817655",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# How many Uber trips occurred during the timestamp in the dataset?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "db49f0cb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:31.912636Z",
     "iopub.status.busy": "2023-09-05T11:55:31.912197Z",
     "iopub.status.idle": "2023-09-05T11:55:31.920251Z",
     "shell.execute_reply": "2023-09-05T11:55:31.918970Z"
    },
    "papermill": {
     "duration": 0.043815,
     "end_time": "2023-09-05T11:55:31.922739",
     "exception": false,
     "start_time": "2023-09-05T11:55:31.878924",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The record start from: 2016-01-13 13:54:00+00:00\n",
      "The record end in: 2016-12-31 22:08:00+00:00\n"
     ]
    }
   ],
   "source": [
    "# Extracting dataset timestamp\n",
    "record_begin = df['START_DATE'].min()\n",
    "record_end = df['START_DATE'].max()\n",
    "print(f'The record start from: {record_begin}')\n",
    "print(f'The record end in: {record_end}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "012bb6c2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:31.986488Z",
     "iopub.status.busy": "2023-09-05T11:55:31.986087Z",
     "iopub.status.idle": "2023-09-05T11:55:31.992117Z",
     "shell.execute_reply": "2023-09-05T11:55:31.990901Z"
    },
    "papermill": {
     "duration": 0.041195,
     "end_time": "2023-09-05T11:55:31.994767",
     "exception": false,
     "start_time": "2023-09-05T11:55:31.953572",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total trips recorded: 1112 trips\n"
     ]
    }
   ],
   "source": [
    "# Extracting how much trip recorded in the dataset\n",
    "print(f'Total trips recorded: {len(df)} trips')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ef60be7",
   "metadata": {
    "papermill": {
     "duration": 0.030554,
     "end_time": "2023-09-05T11:55:32.056737",
     "exception": false,
     "start_time": "2023-09-05T11:55:32.026183",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Insights\n",
    "\n",
    "- The data records 1154 trips\n",
    "- The data start to record trips from 1 Jan 2016 to 31 Dec 2016 (1-year timestamp)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0503c49d",
   "metadata": {
    "papermill": {
     "duration": 0.031214,
     "end_time": "2023-09-05T11:55:32.119243",
     "exception": false,
     "start_time": "2023-09-05T11:55:32.088029",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# What is the median for daily and monthly total trips?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "96cbabc8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:32.183211Z",
     "iopub.status.busy": "2023-09-05T11:55:32.182828Z",
     "iopub.status.idle": "2023-09-05T11:55:32.235241Z",
     "shell.execute_reply": "2023-09-05T11:55:32.234147Z"
    },
    "papermill": {
     "duration": 0.087507,
     "end_time": "2023-09-05T11:55:32.237791",
     "exception": false,
     "start_time": "2023-09-05T11:55:32.150284",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>START_DATE</th>\n",
       "      <th>END_DATE</th>\n",
       "      <th>CATEGORY</th>\n",
       "      <th>START_POINT</th>\n",
       "      <th>STOP_POINT</th>\n",
       "      <th>MILES</th>\n",
       "      <th>PURPOSE</th>\n",
       "      <th>HOUR</th>\n",
       "      <th>MONTH</th>\n",
       "      <th>DATE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>Business</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>5.1</td>\n",
       "      <td>Meal/Entertain</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>Business</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>Fort Pierce</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  START_DATE END_DATE  CATEGORY  START_POINT   STOP_POINT  MILES  \\\n",
       "0        NaT      NaT  Business  Fort Pierce  Fort Pierce    5.1   \n",
       "1        NaT      NaT  Business  Fort Pierce  Fort Pierce    5.0   \n",
       "\n",
       "          PURPOSE HOUR MONTH DATE  \n",
       "0  Meal/Entertain  NaN   NaN  NaN  \n",
       "1             NaN  NaN   NaN  NaN  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Copying dataframe\n",
    "median_trip_data = df.copy()\n",
    "\n",
    "# Extracting Hour, Month, and Date information\n",
    "median_trip_data['HOUR'] = median_trip_data['START_DATE'].apply(lambda x: x.strftime('%H'))\n",
    "median_trip_data['MONTH'] = median_trip_data['START_DATE'].apply(lambda x: x.strftime('%b'))\n",
    "median_trip_data['DATE'] = median_trip_data['START_DATE'].apply(lambda x: x.strftime('%Y-%m-%d'))\n",
    "\n",
    "# Checking the data\n",
    "median_trip_data.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "fe07ca92",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:32.303607Z",
     "iopub.status.busy": "2023-09-05T11:55:32.303209Z",
     "iopub.status.idle": "2023-09-05T11:55:32.315058Z",
     "shell.execute_reply": "2023-09-05T11:55:32.313427Z"
    },
    "papermill": {
     "duration": 0.047753,
     "end_time": "2023-09-05T11:55:32.317457",
     "exception": false,
     "start_time": "2023-09-05T11:55:32.269704",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median of total orders per month: 68.0 orders\n",
      "Median of total orders per day: 3.0 orders\n"
     ]
    }
   ],
   "source": [
    "# Calculating median of total orders per month\n",
    "median_trip_per_month = median_trip_data.groupby(['MONTH']).size().median()\n",
    "\n",
    "# Calculating median of total orders per day\n",
    "median_trip_per_day = median_trip_data.groupby(['DATE']).size().median()\n",
    "\n",
    "print(f'Median of total orders per month: {median_trip_per_month} orders')\n",
    "print(f'Median of total orders per day: {median_trip_per_day} orders')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37e121f0",
   "metadata": {
    "papermill": {
     "duration": 0.031086,
     "end_time": "2023-09-05T11:55:32.379954",
     "exception": false,
     "start_time": "2023-09-05T11:55:32.348868",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Insights\n",
    "In 2016, there were approximately\n",
    "\n",
    "- 110 orders each month (based on median measurement)\n",
    "- 4 orders each day (based on median measurement)\n",
    "- or we can say that there is 1 order for every 6-hour"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af85b54a",
   "metadata": {
    "papermill": {
     "duration": 0.031005,
     "end_time": "2023-09-05T11:55:32.443807",
     "exception": false,
     "start_time": "2023-09-05T11:55:32.412802",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# How is the customer segment proportion?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "204443e6",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:32.510034Z",
     "iopub.status.busy": "2023-09-05T11:55:32.509579Z",
     "iopub.status.idle": "2023-09-05T11:55:32.789294Z",
     "shell.execute_reply": "2023-09-05T11:55:32.788439Z"
    },
    "papermill": {
     "duration": 0.31546,
     "end_time": "2023-09-05T11:55:32.791846",
     "exception": false,
     "start_time": "2023-09-05T11:55:32.476386",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculating CATEGORY column proportion\n",
    "category_proportions = df['CATEGORY'].value_counts(normalize=True)\n",
    "\n",
    "# Creating figure and axes object\n",
    "fig, ax = plt.subplots(figsize = (12,6))\n",
    "\n",
    "# Plotting\n",
    "sns.barplot(x = category_proportions.index, \n",
    "            y = category_proportions.values,\n",
    "            ax = ax\n",
    "           )\n",
    "\n",
    "# Customize the plot\n",
    "plt.xlabel('Category')\n",
    "plt.ylabel('Proportion')\n",
    "plt.title('Customer Segment Proportion\\n01 Jan 2016 - 31 Dec 2016')\n",
    "\n",
    "# Add proportion numbers at the top of each bar\n",
    "for p in ax.patches:\n",
    "    height = p.get_height()\n",
    "    ax.text(p.get_x() + p.get_width() / 2., height, f'{height:.2f}', ha='center', va='bottom')\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "238a37f5",
   "metadata": {
    "papermill": {
     "duration": 0.0313,
     "end_time": "2023-09-05T11:55:32.854790",
     "exception": false,
     "start_time": "2023-09-05T11:55:32.823490",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "As we can see from the previous insights, the customer segments are divided into more detailed segmentation with the help of the `PURPOSE` column. So let's see its distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "b3885bb3",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:32.920142Z",
     "iopub.status.busy": "2023-09-05T11:55:32.919510Z",
     "iopub.status.idle": "2023-09-05T11:55:33.291204Z",
     "shell.execute_reply": "2023-09-05T11:55:33.290074Z"
    },
    "papermill": {
     "duration": 0.40724,
     "end_time": "2023-09-05T11:55:33.293676",
     "exception": false,
     "start_time": "2023-09-05T11:55:32.886436",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculating PURPOSE column proportion\n",
    "purpose_proportion = df['PURPOSE'].value_counts(normalize=True)\n",
    "\n",
    "# Creating figure and axes object\n",
    "fig, ax = plt.subplots(figsize=(12,6))\n",
    "\n",
    "# Plotting\n",
    "sns.barplot(\n",
    "    x = purpose_proportion.values,\n",
    "    y = purpose_proportion.index,\n",
    "    ax = ax\n",
    ")\n",
    "\n",
    "# Customizing\n",
    "plt.title('Customer Segment Proportion\\n01 Jan 2016 - 31 Dec 2016')\n",
    "plt.xlabel('Proportions')\n",
    "plt.ylabel('Segments')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "395fb415",
   "metadata": {
    "papermill": {
     "duration": 0.032368,
     "end_time": "2023-09-05T11:55:33.358650",
     "exception": false,
     "start_time": "2023-09-05T11:55:33.326282",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Insights\n",
    "\n",
    "- Throughout 2016, **~93% of the customers used Uber for Business occasions**, compared to **only ~7% who used it for Personal use**.\n",
    "- The top 3 purpose for our customers to order Uber is Meeting, Meal/Entertain, and Errand/Supplies, all of which lies in the category of Business.\n",
    "- If from the very first start, the company does prioritize targeting business people, this result wouldn't be so much of a concern. However, if the company also indeed target Personal use customer, this result is concerning and thus needs to be investigated more."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52b2d0f8",
   "metadata": {
    "papermill": {
     "duration": 0.032476,
     "end_time": "2023-09-05T11:55:33.425955",
     "exception": false,
     "start_time": "2023-09-05T11:55:33.393479",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# How is the hourly trend for Uber trips?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "2603825d",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:33.494205Z",
     "iopub.status.busy": "2023-09-05T11:55:33.493509Z",
     "iopub.status.idle": "2023-09-05T11:55:33.957710Z",
     "shell.execute_reply": "2023-09-05T11:55:33.956503Z"
    },
    "papermill": {
     "duration": 0.500798,
     "end_time": "2023-09-05T11:55:33.960371",
     "exception": false,
     "start_time": "2023-09-05T11:55:33.459573",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Copy dataset\n",
    "hourly_data = df.copy()\n",
    "\n",
    "# Crete hour column\n",
    "hourly_data['HOUR'] = hourly_data['START_DATE'].apply(lambda x: x.strftime('%H'))\n",
    "\n",
    "# Counting data in each column\n",
    "hourly_data_count = hourly_data.groupby(['HOUR']).size().reset_index(name='COUNT')\n",
    "\n",
    "# Plotting trend\n",
    "\n",
    "# Creating figure and axes object\n",
    "fig, ax = plt.subplots(figsize=(12,6))\n",
    "\n",
    "# Ploting\n",
    "sns.lineplot(\n",
    "    data = hourly_data_count,\n",
    "    x = 'HOUR',\n",
    "    y = 'COUNT',\n",
    "    ax = ax,\n",
    "    label = 'Total Orders',\n",
    "    marker = '.',\n",
    "    markersize = 12\n",
    ")\n",
    "\n",
    "# Customizing\n",
    "ax.set_title('Uber Order Trend by Hour\\n01 Jan 2016 - 31 Dec 2016')\n",
    "ax.set_ylabel('Orders Count')\n",
    "ax.set_xlabel('Hour')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8fc21c4",
   "metadata": {
    "papermill": {
     "duration": 0.033074,
     "end_time": "2023-09-05T11:55:34.027258",
     "exception": false,
     "start_time": "2023-09-05T11:55:33.994184",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Insights\n",
    "- The orders start to increase at 6 a.m.\n",
    "- There are a relatively high amount of orders starting from 1 pm to 6 pm.\n",
    "- Apparently, there was no Uber order made at the time interval 4 a.m. - 5 a.m. in 2016."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3902112",
   "metadata": {
    "papermill": {
     "duration": 0.033012,
     "end_time": "2023-09-05T11:55:34.093666",
     "exception": false,
     "start_time": "2023-09-05T11:55:34.060654",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# How are the conditional probabilities of each segment ordering an Uber for each hour?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "9d2196fb",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:34.162468Z",
     "iopub.status.busy": "2023-09-05T11:55:34.162064Z",
     "iopub.status.idle": "2023-09-05T11:55:35.256175Z",
     "shell.execute_reply": "2023-09-05T11:55:35.254247Z"
    },
    "papermill": {
     "duration": 1.131956,
     "end_time": "2023-09-05T11:55:35.259098",
     "exception": false,
     "start_time": "2023-09-05T11:55:34.127142",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1400x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Copying df\n",
    "hourly_segment_proba = df.copy()\n",
    "\n",
    "# Crete hour column\n",
    "hourly_segment_proba['HOUR'] = hourly_segment_proba['START_DATE'].apply(lambda x: x.strftime('%H'))\n",
    "\n",
    "# Groupby hour and purpose\n",
    "hourly_segment_proba = hourly_segment_proba.groupby(['HOUR', 'PURPOSE']).size().div(len(df)).reset_index(name='PROBABILITY')\n",
    "\n",
    "# Compute the contingency table\n",
    "contingency_table = pd.crosstab(hourly_segment_proba['PURPOSE'], hourly_segment_proba['HOUR'], normalize='columns')\n",
    "\n",
    "# Creating figure\n",
    "plt.figure(figsize=(14, 6))\n",
    "\n",
    "# Plotting\n",
    "sns.heatmap(contingency_table, annot=True, cmap='Blues', fmt='.2f')\n",
    "\n",
    "# Customizing\n",
    "plt.xlabel('Hour')\n",
    "plt.ylabel('Purpose')\n",
    "plt.title('Segments Probability by Hour\\n01 Jan 2016 - 31 Dec 2016')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80c566fc",
   "metadata": {
    "papermill": {
     "duration": 0.03479,
     "end_time": "2023-09-05T11:55:35.330229",
     "exception": false,
     "start_time": "2023-09-05T11:55:35.295439",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Insights\n",
    "\n",
    "By knowing the probability of someone ordering an Uber at a certain time, we can gain information about what kind of customers that most likely to order an Uber at that time. This information would be useful for the Uber company or the drivers as they can supply and prepare the resources needed to accommodate the customer's purposes.\n",
    "\n",
    "- At 3 a.m., the possibility of a person ordering an Uber is for a Meeting, a Customer Visit, or Errand/Supplies.\n",
    "- At 5 a.m., the possibility for someone ordering an Uber is either for a Meeting or for a Meal/Entertain.\n",
    "\n",
    "So maybe at around 5 am-6 am, drivers could stand by in the office area or residential area so that they can pick up customers who are most likely in that time would have a Meeting or a Meal/Entertain purposes. To be more precise and connect more information, we can see the top pickup point preferences for each segment (purpose) based on the `START_POINT` column."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6f754f2",
   "metadata": {
    "papermill": {
     "duration": 0.03462,
     "end_time": "2023-09-05T11:55:35.400533",
     "exception": false,
     "start_time": "2023-09-05T11:55:35.365913",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# What are the favorite pick-up spots for each segment?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "5e7be99f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:35.473584Z",
     "iopub.status.busy": "2023-09-05T11:55:35.473185Z",
     "iopub.status.idle": "2023-09-05T11:55:35.482382Z",
     "shell.execute_reply": "2023-09-05T11:55:35.481242Z"
    },
    "papermill": {
     "duration": 0.048281,
     "end_time": "2023-09-05T11:55:35.484742",
     "exception": false,
     "start_time": "2023-09-05T11:55:35.436461",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extracting axes size\n",
    "len(df['PURPOSE'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "65c265e1",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:35.562161Z",
     "iopub.status.busy": "2023-09-05T11:55:35.561722Z",
     "iopub.status.idle": "2023-09-05T11:55:37.896698Z",
     "shell.execute_reply": "2023-09-05T11:55:37.895553Z"
    },
    "papermill": {
     "duration": 2.377377,
     "end_time": "2023-09-05T11:55:37.899922",
     "exception": false,
     "start_time": "2023-09-05T11:55:35.522545",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1100 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creating figure and axes object\n",
    "fig, axs = plt.subplots(nrows = 5, ncols = 2, figsize = (12,11))\n",
    "\n",
    "# Flatten the axs array\n",
    "axs = axs.flatten()\n",
    "\n",
    "# Extracting PURPOSE column categories\n",
    "cat = df['PURPOSE'].unique()\n",
    "\n",
    "# Zipping ax and categories\n",
    "pair = tuple(zip(axs, cat))\n",
    "\n",
    "# Plotting\n",
    "for ax, cat in pair:\n",
    "    if type(cat) == float:\n",
    "        continue\n",
    "    else:\n",
    "        data = df.groupby(['PURPOSE', 'START_POINT']).size().reset_index(name='count').sort_values(by='count', ascending = False)\n",
    "        sns.barplot(\n",
    "            data = data.loc[data['PURPOSE'] == cat].head(5),\n",
    "            x = 'START_POINT',\n",
    "            y = 'count',\n",
    "            ax = ax\n",
    "        )\n",
    "        ax.set_title(f'Top 5 Pick-up Spots for {cat}')\n",
    "    \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "313105cc",
   "metadata": {
    "papermill": {
     "duration": 0.036827,
     "end_time": "2023-09-05T11:55:37.973501",
     "exception": false,
     "start_time": "2023-09-05T11:55:37.936674",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Insights\n",
    "\n",
    "Now we can correlate this information with our previous insight. For example\n",
    "\n",
    "- At 5 a.m., drivers can stand by at Carry, Durham, Morrisville, or Whitebridge because the possibility of getting an order is great at that time and place. (Remember our insights on the previous question which states that, at 5 a.m. the order possibilities only come from customers who have a Meeting purpose or Meal/Entrtain purpose.\n",
    "- This information also helps Uber and its drivers understand the customer's behaviors, specifically their location-ordering behavior."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7db084a8",
   "metadata": {
    "papermill": {
     "duration": 0.036993,
     "end_time": "2023-09-05T11:55:38.048167",
     "exception": false,
     "start_time": "2023-09-05T11:55:38.011174",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# How is the daily trend for Uber trips?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "7a958670",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:38.126058Z",
     "iopub.status.busy": "2023-09-05T11:55:38.125233Z",
     "iopub.status.idle": "2023-09-05T11:55:38.491202Z",
     "shell.execute_reply": "2023-09-05T11:55:38.490075Z"
    },
    "papermill": {
     "duration": 0.408427,
     "end_time": "2023-09-05T11:55:38.493788",
     "exception": false,
     "start_time": "2023-09-05T11:55:38.085361",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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oQX5+Pjt37mTu3LnUrl37gu385emf//wnW7Zs4dFHH+W9996jT58+1KlTh71797JhwwaWLl3KRx99RHJy8kW/xp///GdmzpzJyy+/zLJly+jTpw/79u3jk08+YdiwYUycONHv5xw5ciSjR49m9OjRNGvWjNWrVzN58mQSEhJ49dVXS3zMddddR2JiIvv27aN27dpce+21F/V+0tPTvb+AyM/P59ChQyxfvpzly5cDnhn2n+6vftttt/HCCy/w4IMPMnv2bJo3b86WLVv49ttvufbaa/nkk0/O+XqByi0iIgFQPjvLiYhIVZSVlWWffvpp26VLFxsbG2tDQ0NtYmKiHT58uJ04cWKJjyna43vWrFn27bff9u6zXqtWLXvHHXcU24v87Nd65plnbOfOnW10dLStVq2aTUpKssOGDbP/+c9/fPZEL9p3+6233rro95adnW1ffPFF27t3b1ujRg0bFhZm69SpY4cPH24/+eQT63a7S3xc48aNi+2l/VPTpk2zvXv3tpGRkTY+Pt6OHDnSbtiwwbu/+dn7tBdZs2aNvf32222jRo1seHi4rVGjhm3btq29++677cyZM32uLdpf/VJdaJ/2nx4/W25urv3HP/5he/bsaatXr27Dw8Ntw4YNbf/+/e1LL73ks0940V7l59pX/Vyf03379tmf//zntlatWrZatWq2Q4cO9q233rrg8/3U2ePl22+/tT169LBRUVE2Li7OXnvttXbTpk3nffyDDz5oAfvb3/62VK93trP3qC/6U61aNVu3bl175ZVX2ocfftiuXLnynI9ft26dvfrqq23t2rVtVFSU7dy5s3399ddtWlqaBeztt99eJrlFRCRwjLU/6VkUERERkYDp27cv8+bNY/PmzTRr1szpOKVWUXOLiFQ2uqddREREpIwsWrSIuXPnMmTIkApV+FbU3CIilZHuaRcREREJsH/+85/s3r2bd955h5CQEJ588kmnI5VKRc0tIlKZqT1eREREJMCSkpLYvXs3zZo148knn2Ts2LFORyqVippbRKQyU9EuIiIiIiIiEqR0T7uIiIiIiIhIkFLRLiIiIiIiIhKkVLSLiIiIiIiIBCkV7SIiclF2797NuHHjqF+/PhERESQlJTF+/HiOHj1a7Nr8/Hz+/ve/8/Of/5yOHTsSHh6OMYY33njD79dNT0/HGENSUlIA3kVgWGuZOnUq9913Hx07diQhIYFq1arRokULxo8fz4EDB8752CNHjjB+/HiSkpKIiIigfv36jBs3jt27d5d4/X//+19++ctf0r17d6KiojDG8L//+78XzJifn88rr7xC9+7diYuLIzo6mhYtWnDbbbdx8ODBi37vpfH1119zww030KpVK2rUqEFkZCTNmzfnpptuYtmyZSU+Zvr06Tz00EMMGDCAhIQEjDH06dPnol4/NTUVY4z3T2hoKAkJCbRu3ZobbriBd955hxMnTlzKWwwojScRETmbFqITERG/bdu2jV69epGRkcGoUaNo1aoVS5YsYdasWbRs2ZL58+dTs2ZN7/WZmZnUqFEDgDp16hAeHs6uXbt4/fXXueuuu/x67fT0dJKTk2ncuDHp6emBfFsX7dSpU0RGRhIWFkZKSgrt27fH7Xbz/fffs2bNGurUqcMPP/xAixYtfB53+PBhevXqxebNm+nfvz/dunVj48aNTJgwgcTERBYuXEiTJk18HhMfH8+xY8eoUaMGCQkJbNu2jT/96U88/fTT58x35MgRhg4dypIlS+jcuTN9+/b1fg1mz57NtGnTaNeuXZl8bgB+/vOfM2fOHLp160b9+vUJDw9n69atTJo0iby8PF577bVi4+Caa65hwoQJVKtWjWbNmrF27Vp69+7NvHnz/H791NRU5syZw+23305SUhLWWrKyskhLS+OHH37g6NGj1K9fnzfffJPBgwcH6m1fNI0nERHxYUVERPw0aNAgC9hXXnnF5/iDDz5oAfvLX/7S53hubq6dPHmy3bt3r7XW2scee8wC9vXXX/f7tdPS0ixgGzdufNH5Ay0vL88+9dRT9tChQz7HCwsL7S9/+UsL2OHDhxd73N13320B++CDD/oc//vf/24BO3jw4GKPmTJlik1PT7fWWvvWW29ZwP7pT386b75hw4ZZwL766qvFzrndbltQUHDB93gpcnJySjy+Zs0aGxERYatXr25zc3N9zi1YsMCuXbvWFhQUeL/mvXv3vqjXT0lJsYCdNWtWidmefvpp63K5bHh4uJ07d+5FvUYgaTyJiMjZVLSLiIhftm7dagGbnJxsCwsLfc5lZWXZ6OhoGxkZaY8fP37O5yiLoj03N9f+4x//sEOHDrWNGjWy4eHhNj4+3vbv399+++23JT5X48aNbePGje2JEyfsww8/bBs2bGjDw8Nt06ZN7bPPPmvdbrff+X5qz549FrDR0dE+x48fP24jIyNtTEyMzcrK8jlXWFhok5KSLGC3bdt2zucuTZE1Y8YMC9gxY8Zc2hspIx07drSA3bNnzzmvKcuivcijjz5qAdupU6di5/Lz8+3//d//2e7du9vY2FgbGRlpO3bsaP/xj38U+3+gyOLFi+3YsWNt/fr1bXh4uK1bt64dOHCg/eSTTy7qPRTReBIRqXp0T7uIiPhl1qxZAAwaNAiXy/fHSGxsLL179yYnJ4fFixeXa64jR47wwAMPcPz4cQYOHMj/+3//j1GjRrFixQpGjBjBa6+9VuLj8vPzGTRoEF988QVDhw7lrrvuIicnhz/84Q88/vjjl5wrPDwcgLCwMJ/jixYtIicnh969exMbG+tzzuVyMWjQIODM5/tiffTRRwDccccdHDhwgP/+9788++yzvPXWW+zZs+eSnvtSbd68mU2bNlG7dm3q1q3raJaHH36YyMhIVq5cyfr1673H8/PzGTFiBPfeey/Hjh3j5ptv5u6778btdnPfffdx2223FXuu119/nV69evH111/Tq1cvHnroIYYPH86BAwd49dVXLymnxpOISNUT6nQAERGpWDZt2gRA8+bNSzzfvHlzpk2bxubNmxkwYEC55apRowY7duzgsssu8zl+9OhRevfuze9//3tuvfVWIiMjfc7v3buXDh06MH36dO+5xx57jBYtWvDyyy/zv//7v8UKJH/897//BWDIkCE+x0vzeQRPYXspli5dCsCWLVu44YYbfBZcCwsL49FHHy3VwmOBMGPGDObNm0deXh5paWl88803GGP473//W+wXQOUtNjaWLl26MG/ePJYsWUKbNm0AeOaZZ/juu+944IEHePHFFwkJCQGgsLCQu+++mzfffJMxY8ZwzTXXALB+/Xp+/etfU716debOnUvbtm19XmfXrl2XlFPjSUSk6tFMu4iI+OXYsWMAxMXFlXi+6HhmZmZ5RQIgIiKiWMEOnmL+zjvv5OjRo96C46f+8Y9/+BTziYmJjBo1iqysLG8xdDGWLl3KE088QUxMTLGFvcrr85iRkQF4ZpKvv/56tm7dSmZmJl9++SU1atTgkUce4e23376k1yitGTNm8MQTT/Dss8/y8ccfExsby9dff83VV19dLq9/IfXr1wfOfM7cbjf//Oc/qVevnk/BDhASEsKLL76IMYYPPvjAe/xf//oXBQUFPPLII8UKdoCGDRtedD6NJxGRqkkz7SIiElD29KYkxphyf+1169bxwgsv8MMPP7Bv3z5OnTrlc76k9t34+HiaNm1a7HhRcVXSFnalsWnTJq6++mry8/P54IMPSnyN8wnU57GwsBCALl268Oabb3qfb/To0YSGhjJy5EieffZZ7rjjjvM+T3p6eonFmD+3EDz33HM899xznDhxgs2bN/PXv/6VwYMH89RTT/GnP/2p1M9TXjZv3szhw4dp3rw5Tz31VInXREZGsnHjRu/HixYtAmDo0KEBzVLZxpOIiJSeinYREfFL0Yxd0czeT2VlZflcV14WLVpE//79KSgoYMCAAYwcOZLq1avjcrlYtWoVEyZMIDc3t9jjzpUzNNTzI7KoSPHHxo0b6d+/P0eOHOHjjz9m9OjR53zdsv481qhRg4MHDzJy5MhiBdvw4cMJDw9n8+bNHDt27LyvlZ6ezhNPPFHs+MXc9x8dHU2nTp344IMPOHLkCI888giDBg2iW7dufj9XIO3duxeA2rVrA54t1MDTCl7Sey+SnZ3t/XvRTHaDBg0ClqsyjicRESk9tceLiIhfWrZsCZz73tgtW7YAFNtDuqw9/fTT5OTkMG3aNKZMmcLLL7/Mk08+yeOPP0737t3LLce6detITU3l8OHDfPbZZ1x33XUlXlden8ei14mPjy92zuVyUb16dQBycnLO+zypqalYz64zPn8u1ZAhQ7DWMmfOnEt+rktx/Phxli9fDkCPHj2AMwXu6NGjS3zvRX/S0tK8z1P0eQ7UomyVdTyJiEjpqWgXERG/9OvXD4Bp06bhdrt9zh0/fpz58+cTGRnpLXzKy9atW0lISCA1NbXYufIqCNesWUO/fv3IzMzkiy++YNSoUee8tkePHkRGRjJ//nyOHz/uc87tdjNt2jTgzOf7YhUtBrhu3bpi5w4cOMChQ4eIjo6mVq1al/Q6F6uouC3qbHDKCy+8QE5ODp06daJ169YAtGrVivj4eBYtWkR+fn6pnqdo3H/33XeXnEnjSUREQEW7iIj4qWnTpgwaNIj09HT+7//+z+fcY489xokTJ7jtttuIjo4u11xJSUkcOXKENWvW+Bz/73//G5AC6kJWrVpF//79yc7OZsKECYwYMeK818fExHDrrbdy4sSJYi3m//znP0lPT2fw4ME0adLkknLdcsstxMfH88477/gUWm63m9/+9rcAjBkzpsyK5tzcXBYsWFDiuaVLl/Lvf/8bl8tVbDX08nLq1Cn+/Oc/88wzzxAeHs4rr7ziPRcaGsp9993Hvn37uP/++0ucPd63b5/PFnH33HMPoaGhPPnkkz73uhfZvXt3qXJpPImISBFjA9HbJiIiVcq2bdvo1asXGRkZjBo1itatW7N48WJmzZpFixYtWLBgATVr1vR5zHPPPectYlatWsXq1avp1auXdyuqPn36cNddd13wtdPT00lOTqZx48akp6d7j0+dOpWhQ4cSGxvL2LFjiYuLY9myZcybN49rr72Wzz//nLfeestngaykpCTvc/7U448/zhNPPMGsWbNKnL0/29GjR2nWrBlHjhxhwIAB9OnTp8Trxo8f79NWfPjwYXr16sXmzZvp378/V1xxBRs2bGDChAkkJiayYMGCYguOvfHGG8ybNw/wdBfMnz+f9u3b06lTJ8AzO/z73//e5zGfffYZN954I9WqVePaa6+ldu3azJkzhxUrVtCsWTMWLFjgvY870DIzM6lRowatWrWic+fOXHbZZZw8eZINGzbw/fffA55Z7oceesjncfPmzeONN94APPeMf/HFFyQmJvos8FbaVcpTU1OZM2cOt99+u/drnp2dzbZt2/jhhx84cuQI9erV48033yz2y4P8/HzGjBnDxIkTadCgAf3796dBgwZkZGSwZcsW5s+fzzPPPOPzOX/99df51a9+RVhYGCNHjqR58+YcOnSIpUuXEhcXd8G90jWeRETEhxUREbkIO3futHfccYetW7euDQsLs40aNbL333+/PXz4cInXp6SkWOCcf26//fZSve7WrVstYJs3b17s3DfffGO7d+9uY2JibFxcnB04cKCdM2eOfeuttyxg33rrLZ/rGzdubBs3blzi6zz22GMWsLNmzbpgprS0tPO+t6I/aWlpxR57+PBhe//999tGjRrZsLAwW7duXfvzn//c7tq1q8TXuv3228/7GikpKSU+bv78+Xb48OE2ISHBhoWF2SZNmtiHHnrIHjly5ILv71Lk5eXZJ5980g4YMMA2aNDARkRE2GrVqtmmTZvaW2+91S5atKjExxV9zc73p7R+OvZCQkJsXFycbdmypR07dqx96623bHZ29jkf73a77bvvvmv79+9va9SoYcPCwmz9+vVt79697TPPPGN37txZ7DELFiyw1157ra1du7YNCwuz9erVs4MHD7afffbZBfNqPImIyNk00y4iIhXKwoUL6dWrF7179/bOEIqIiIhUVrqnXUREKpSvvvoKoNwXuhMRERFxgmbaRUQk6GVmZvLCCy+wevVqJk2aRGxsLGvWrPHenywiIiJSWaloFxGRoJeenk6TJk2Ij4+nd+/ePPXUU3Ts2NHpWCIiIiJlTkW7iIiIiIiISJDSPe0iIiIiIiIiQUpFu4iIiIiIiEiQUtEuIiIiIiIiEqRUtIuIiIiIiIgEqVAnX3z9+vVMnDiRtLQ0jh49ysMPP8wVV1wBQEFBAR9//DErV64kIyODqKgoLr/8cm6++WYSEhK8z5Gfn897773H/PnzycvLo127dtx1113UrFnT7zxHjx6loKAgYO+vLNSuXZuDBw86HUMqEI0Z8ZfGjPhLY0b8pTEj/tKYEX9VhDETGhpKjRo1LnxdOWQ5p9zcXJKSkujXrx8vvviiz7m8vDzS0tK47rrrSEpKIjs7m3feeYe//OUvPPfcc97r3n77bZYvX84DDzxAbGws7777Ls899xzPP/88Lpd/jQQFBQXk5+cH5L2VBWMM4MmpRf+lNDRmxF8aM+IvjRnxl8aM+EtjRvxV2caMo0V7p06d6NSpU4nnoqKieOSRR3yO/fznP+ePf/wjhw4dolatWpw8eZLvv/+e++67j/bt2wNw3333cc8997BmzRrt4SsiIiIiIiIVmqNFu79OnjyJMYaoqCgAtm/fTmFhobdgB0hISKBRo0Zs3rz5nEV7fn6+z4y6MYbIyEjv34NVUbZgzijBRWNG/KUxI/7SmBF/acyIvzRmxF+VbcxUmKI9Ly+PDz/8kN69e3uL9szMTEJDQ4mJifG5Ni4ujszMzHM+11dffcXnn3/u/Tg5OZnnn3+e2rVrl0n2QKtbt67TEaSC0ZgRf2nMiL80ZsRfGjPiL40Z8VdlGTMVomgvKCjg5ZdfxlrLXXfddcHrL3TfwujRoxkxYoT346LfwBw8eDCoF6IzxlC3bl32799fKe7NkLKnMSP+0pgRf2nMiL80ZsRfGjPir4oyZkJDQ0s1cRz0RXtBQQEvvfQSBw8e5NFHH/XOsgPEx8dTUFBAdna2z2x7VlYWLVu2POdzhoWFERYWVuK5YP6iFrHWVoicEjw0ZsRfGjPiL40Z8ZfGjPhLY0b8VVnGTFDv015UsO/fv59HHnmE2NhYn/NNmjQhJCSENWvWeI8dPXqUnTt30qJFi/KOKyIiIiIiIhJQjs60nzp1iv3793s/zsjIID09nZiYGGrUqMHf/vY30tLS+N3vfofb7fbepx4TE0NoaChRUVH079+f9957j9jYWGJiYnjvvfdo1KiRz+J0IiIiIiIiIhWRo0X7tm3beOKJJ7wfv/vuuwCkpKRw/fXXs2zZMgB++9vf+jzuscceo23btgDcfvvthISE8NJLL5GXl0e7du343e9+5/ce7SIiIiIiIiLBxtGivW3btnz66afnPH++c0XCw8MZN24c48aNC2Q0EREREREREcdpOlpEREREREQkSKloFxEREREREQlSKtpFREREREREgpSKdhEREREpNyEhIT7/FRGR83N0IToRERERqRoiIyOJDg0hJDSUgox91IyNo7CggBMFheTk5DgdT0QkaKloFxEREZEyVT0qkoi8Uxx79SVyFs+BwkIICSGyewpxv3iQsKhIsk6qcBcRKYna40VERESkzERGegr2jAd+Rs6C7z0FO0BhITkLvifjgZ8RkZdLZGSks0FFRIKUinYRERERKTPRoSEce/0l3FnHSjzvzjrGsTdeIjpU97iLiJRERbuIiIiIlImQEM897DmL55z3upxFswkJDdXidCIiJVDRLiIiIiJlwuVy4c7KPNMSfy6FhbizjuFy6Z+mIiI/pe+MIiIiIlIm3G43rurxcKEZ9JAQXNXjcLvd5ZJLRKQiUdEuIiIiImWisLCQwoICIrunnPe6yB6pFBYUUHihGXkRkSpIRbuIiIiIlJkTBYXE/eJBXNXjSjzvqh5H3F0PcqJABbuISElUtIuIiIhImcnJySE3rBqJf32TyN4DzrTKh4QQ2XsAiX9/n9zwCHJytE+7iEhJQp0OICIiIiKV27EfV1BtyRyq3zCOGg8+ij1+HFMtksKMvRzftZNT9Ro6HVFEJGhppl1EREREypRdNo+TsyaT8eEbHD5+gtDEumR8+xkHHriVE++/6nQ8EZGgpqJdRERERMqMdbuxy+cDYLr28S42Zzt0B5cLNq/D7tnhZEQRkaCmol1EREREys62jZB5BCKjoU1H72GTUAs6dgfAzp7iUDgRkeCnol1EREREyoxdNg8A07E7JizM55wrdZjnmoWzsDknyz2biEhFoKJdRERERMqEdRdily8AwHTtXfyCVu2hbgPIzcEuml2+4UREKggV7SIiIiJSNrZugGPFW+OLGGMwRbPtsydjrS3ffCIiFYCKdhEREREpE3bZ6QXoOvXAhIaVeI3p2R/CI2DvTti8rjzjiYhUCCraRURERCTgrLsQu6KoNb7POa8zUdGYHqmex8yeXB7RREQqFBXtIiIiIhJ4WzbAsaMQFQOt25/3Um+L/MqF2Mwj5RBORKTiUNEuIiIiIgHnXTX+PK3xRUzDZGjWGgoLsXOnlUc8EZEKQ0W7iIiIiASUZ9X40/ezn6c1/mze2fYfpmILCsoqmohIhaOiXUREREQCa/M6OH4MomM927qVguncC2LjIPMIrFlSxgFFRCoOFe0iIiIiElDe1vjOPTGhoaV6jAkLw1w5CAD3LC1IJyJSREW7iIiIiASMLSzErlgIgOnS26/Hmr6Dwbhg4xrsvl1lEU9EpMJR0S4iIiIigbN5rac1PiYWWl7u10NNzURo3xUAO2dqWaQTEalwVLSLiIiISMDYZacXoOtU+tb4s7n6Dfc8z4KZ2FM5Ac0mIlIRqWgXERERkYDwtMYvAEq/anwxrTtAYj3IOYldMieA6UREKiYV7SIiIiISGJt+hOwsiKnud2t8EeNyYVKGAmBnTcZaG8iEIiIVjop2EREREQmIM6vG98KEhFz085jeV0F4OOxOh20bApRORKRiUtEuIiIiIpfMFhRgV55eNb6rf6vG/5SJjsF06+t53llTLjmbiEhFpqJdRERERC7dph8h+zjExkGLdpf8dKbfMADs8vnYrMxLfj4RkYpKRbuIiIiIXLIzrfE9L6k1vohp3AySW0BhAXbutEt+PhGRikpFu4iIiIhcEltQgF1R1Bp/kavGl8Cknp5t/2Eq1l0YsOcVEalIVLSLiIiIyKXZuBpOZp9ujW8bsKc13fpATCwcOQRrlgXseUVEKhIV7SIiIiJySeyy+QCYLr0xrktvjS9iwsIxvQcC4J41OWDPKyJSkahoFxEREZGLZgvysSsXAYFtjS9iUoaAMbB+JfbA3oA/v4hIsFPRLiIiIiIXb8MaT2t8XA1o3jrgT29q14V2XQCwc7T9m4hUPSraRUREROSinVk1vldAW+PP5ira/m3+DGxubpm8hohIsFLRLiIiIiIXpaxb473adoJadeDkCezSH8rudUREgpCKdhERERG5OOtXQc4JiEuAZoFvjS9iXCGY1KEA2FmTsdaW2WuJiAQbFe0iIiIiclG8rfFdemFcZfvPStPrKggNg53bIG1zmb6WiEgwUdEuIiIiIn6z+fnYVYuBMm6NP83EVvfs2w7Y2dr+TUSqDhXtIiIiIuK/9Ssh5yTEJ0DTVuXykqbfcADs0nnY41nl8poiIk5T0S4iIiIifrPL5gNguvQu89Z4r6Tm0LgZFORj508vn9cUEXGYinYRERER8YvNz8OuLr/W+CLGGLwL0s2ZinUXlttri4g4RUW7iIiIiPhn3enW+Bq1oEnLcn1p060vRMXAoQOeHCIilZyKdhERERHxy5lV48uxNf40ExGB6T0AAPcsLUgnIpWfinYRERERKTWbl4tdtQQA07W3IxlMiqdFnrXLsQf3O5JBRKS8qGgXERERkdJbtxJycyChdrm3xhcxdepD205gLXbOVEcyiIiUFxXtIiIiIlJqZ1rje2GMcSyHK3WYJ8/86dj8PMdyiIiUNRXtIiIiIlIqNi8Xu7qoNb78Vo0vUfuuntn+7OPYpfOczSIiUoZUtIuIiIhI6axdAbmnPMVycgtHoxhXCCZlCAB2thakE5HKS0W7iIiIiJSKtzW+ax9HW+OLmD4DISQU0jZjd2x1Oo6ISJlQ0S4iIiIiF2Rzc7FrlgJB0Bp/mqkej+niWcHeavs3EamkVLSLiIiIyIWtXe5pja+ZCEnNnE7jZfqdXpBuyQ/YE9kOpxERCTwV7SIiIiJyQcHWGu/VtBVclgz5edj5M5xOIyIScCraRUREROS8bO6pM63x3YKjNb6IMQbTbygAds4UrNvtcCIRkcBS0S4iIiIi5/fjMsjLhdp1oVFTp9MUY7qnQmQUZOyD9aucjiMiElAq2kVERETkvNxFrfFdegdXa/xpJqIaptcAANza/k1EKhkV7SIiIiJyTjb3lGemneBZNb4kJsXTIs+aZdjDGc6GEREJIBXtIiIiInJOds0yyMs73RrfxOk452TqXQatO4B1Y+dMdTqOiEjAqGgXERERkXMK2lXjS+BKPb0g3bzp2Px8h9OIiASGinYRERERKZE9lVMhWuO9OnSH+Jpw/Bh2xQKn04iIBISKdhEREREpkV2zFPLzILE+NEx2Os4FmZAQTMpgAOysSQ6nEREJjFAnX3z9+vVMnDiRtLQ0jh49ysMPP8wVV1zhPb948WJmzJjB9u3bOX78OH/5y19ISkryeY7HH3+c9evX+xzr1asX48ePL4d3ICIiIlJ5VaTW+CKmzyDst5/Ato3YndsxQXwfvohIaThatOfm5pKUlES/fv148cUXSzzfsmVLevTowX/+859zPs+AAQO44YYbvB+Hh4eXSV4RERGRqsKeOgk/LgfAdOvtcJrSM/EJmE49scvmYedMwdx6r9ORREQuiaNFe6dOnejUqdM5z/ft2xeAjIzzb9sRERFBfHx8IKOJiIiIVGl29VIoyIc6DaBBktNx/GL6DfMU7YtmY6+7HRMV43QkEZGL5mjRHihz585l7ty5xMXF0bFjR66//noiIyPPeX1+fj75Z60oaozxXh/MrV9F2YI5owQXjRnxl8aM+EtjphIrao3v1geXK3DLIJXLmGnRDuo3gr07YeEszFUjy+61pMzp+4z4q7KNmQpftPfp04fExETi4+PZtWsXH374ITt27OCRRx4552O++uorPv/8c+/HycnJPP/889SuXbs8Il+yunXrOh1BKhiNGfGXxoz4S2OmcnGfzGbPupUAJA4dTXi9egF/jbIeM8dH3UTmv57HNW8adX92d6X5x3tVpu8z4q/KMmYqfNF+1VVXef/eqFEj6tWrx+9//3u2b99OkyYlLzwyevRoRowY4f246Jv4wYMHKSgoKNvAl8AYQ926ddm/fz/WWqfjSAWgMSP+0pgRf2nMVE7uRbM9q8bXvYxD4VGYffsC9tzlNWZs284QEUnB7h3snfUdrtYdyuy1pGzp+4z4q6KMmdDQ0FJNHFf4ov2nkpOTCQkJYf/+/ecs2sPCwggLCyvxXDB/UYtYaytETgkeGjPiL40Z8ZfGTOXiXjoXOLM3e1l8bct8zEREYnr2w86ejHvWJEyr9mX3WlIu9H1G/FVZxkyl26d9165dFBYWamE6ERERkYtgT56AdSuAM0V7RWVSh3n+smox9sghR7OIiFwsR2faT506xf79+70fZ2RkkJ6eTkxMDLVq1SI7O5tDhw5x5MgRAPbu3QtAfHw88fHx7N+/n3nz5tGpUydiY2PZvXs37733HsnJybRq1cqR9yQiIiJSkdnVS6CgAOo1xDRo5HScS2IaNPIsSrd5LXbud5hRtzgdSUTEb44W7du2beOJJ57wfvzuu+8CkJKSwr333suyZct49dVXvedffvllAMaMGcPYsWMJDQ3lxx9/ZPLkyZw6dYqaNWvSuXNnrr/++oCucioiIiJSVdiiVeMr+Cx7EZM6DLt5LXbuNOzwsZjQkm+RFBEJVo4W7W3btuXTTz895/nU1FRSU1PPeb5WrVo+Rb+IiIiIXDx7MhtOrxpvuvZ2OE1gmE7dsXE14NhR7MrFmG6V45cRIlJ1aDpaRERERACwqxZDYQHUb4SpX7Fb44uY0DDMlYMBsLMnOZxGRMR/KtpFREREBAC7bD5QeVrji5grB4HLBZvXYffscDqOiIhfVLSLiIiICPZENqxfBVSe1vgiJqEWdOwOgJ09xeE0IiL+UdEuUomFhIT4/FdERORcvK3xDRpj6jV0Ok7AuU5v/2YXzsLmnHQ4jYhI6aloF6mEIiMjqRUbQ83YGAoy9lEzNoZasTFERkY6HU1ERIJUZVs1vphW7aFuA8jNwS6a7XQaEZFSU9EuUslUj4okJv8UWa88zd4b+rHv51ez94Z+ZL3yNDH5p6gepcJdRER82RPHYcMqoPK1xhcxxmCKZttnT8Za62wgEZFSUtEuUolERkYSkXeKjAd+Rs6C76Gw0HOisJCcBd+T8cDPiMjL1Yy7iIj4sCsXeX5mXJaMqXuZ03HKjOnZH8IjYO9O2LzO6TgiIqWiol2kEokODeHY6y/hzjpW4nl31jGOvfES0aG6x11ERM440xpfOWfZi5ioaEyPVMAz2y4iUhGoaBepJEJCQggJDSVn8ZzzXpezaDYhoaFanE5ERACw2VmwYTVQie9nP4u3RX7lQmzmEWfDiIiUgop2kUrAZmdhtm3EffjgmZb4cyksxJ11DJdL//uLiMjp1ni3GxomY+rUdzpOmTMNk6FZaygsxM6d5nQcEZELCnU6gIj4x1oLB/Zgt26ArRuw2zbA/j0U1m+I68W3ICTk/IV7SAiu6nG4s46XX2gREQlalX7V+BKY1GHYrRuwP0zFDh2DCdU/iUUkeOk7lEiQs3m5kL4Vu22jp0DftgGyixfcBW5L4fEsIruneBahO4fIHqkUFhRQeKEZeRERqfTs8SzYuAao/Pezn8107oWNfQMyj8CaJdC5l9ORRETOSUW7SJCxWUc9M+hbN2C3bYQd26CwwPeisHBIaoZp1hrTtA00bYmJqc6JyEjifvEguWuXl7gYnat6HHF3PUh2gQp2ERHx3NeN2w2NmmISK39rfBETFoa5chB28me4Z00mREW7iAQxFe0iDrJuN+zb5dvqfnB/8QvjakDT1pimrTDNWkOjJpjQsGKX5eTkEBYVSeLfP+DYGy+Rs2i2p1U+JITIHqnEjbuf3PAIck7mlP2bExGRoFcVW+OLmL6DsVO+gI1rsPt2Yeo1dDqSiEiJVLSLlCObewq2bzqr1X0T5JzwvcgYqN/IU5w3a41p2hpq1cEYU6rXyDqZQ2RkJNXv+xM1HnzMs0hdZDSF+3eTNfkLTg26FqNF6EREqjx7/Bhs/BGoWq3xRUzNRGjfFVYvwc6ZirnxF05HEhEpkYp2kTJkjxzyFOdFre67tnvaEM8WUQ2SW5xudW8NTVpioqIv6XVzcnLIAUJDQ0lMrMuB9DTyfv9LyDmJqVkH0+3KS3p+ERGp+OyKhWDd0LgZpnZdp+M4wtVvOO7VS7ALZmKv+RmmWqTTkUREilHRLhIgtrAQ9qSf1eq+EY4cLH5hQi1Pcd60tWc2/bIkTBntmV602Jw7ohpm4DXYiR9iJ36E7dIL49I+7SIiVZm3Nb5b1WuN92rdARLrQcY+7JI5mL5DnE4kIlKMinaRi2RPnvBtdd++GXJ/cq+4ywWXJZ/V6t4Kk1DbkbzmqpHYmd/A/t3YxT9gevZzJIeIiDjPZh2FTWsBMF2qXmt8EeNyYVKGYj97EztrMvbKwaW+HU1EpLyoaBcpBWstHDpw+j70jZ7Z9D07wFrfCyOjPO3tRa3uyS2CptXOREZhBo/Gfvku9puPsN2u1L60IiJVlLc1Pqk5plYdp+M4yvS+Cjvhfdid7tlWtVkbpyOJiPjQv9hFSmAL8mFXmmfbta2eQp1jR4pfWLsupmmrM63u9RsGddu56T8CO30CHNyPXfg95spBTkcSEREH2GXzgaq5avxPmegYTLe+2PkzsLOmYFS0i0iQUdEuAtgTx2Grp83dbtsAaVsgP8/3opBQz1ZrRbPoTVth4hOcCXyRTEQ1zNAx2E//i/32E2yPfpiw4lvHiYhI5WWPHYXN64CquWp8SUy/YZ6iffl87A13YqrHOx1JRMRLRbtUOdZaOLDXd1X3fbuKXxgd6ynMi4r0pGaY8IjyDxxgJmUIdtpXcOQgdt40TL/hTkcSEZFy5G2NT27h2fZMMI2bQXILSNuMnTsNM3ys05FERLxUtEulZ/PzYMdW31b37KziF9ZtcFarexuoU79S7mduwiMww8ZiP/w3dtJn2N5XVYpfRoiISOl4V41Xa7wPkzoMm7YZ+8NU7NDrgvp2NxGpWlS0S6VjszK9M+h22wbYsRUKCnwvCg3zLL5zekV3mrbGxFZ3JK8TTJ+B2KlfeGbb50zFDBzldCQRESkHNvMIbDndGl+FV40vienWB/vZf+HIIVizDDp2dzqSiAigol0qOOt2w77d2G3rz7S6Z+wrfmFsnGfLtaJW90ZNq/S93CYsDDPiBuy7/8RO+Rx75aCgWeVeRETKjl2xwLPzSdNWmJrObEEarExYOKb3QOx3X+KeNZkQFe0iEiRUtEuFYnNPQfqWM63u2zfCyRO+FxkD9Rv5rupeu672Xf0J07M/dsrnnpXkZ03CDB3jdCQRESljZ1rjNcteEu+6L+tXYg/sxdSp73QkEREV7RLc7NHDp+9DP12k706DwkLfi8IjPIvpeFd1b4mJinEmcAViQkMxV9+EffMl7NQvsSlDMVHRTscSEZEyYo8ehq0bADCdVbSXxNSuC+26wI/LsHOmYMbe6XQkEREV7RI8rLsQdu/wXdX9cEbxC+NrembPT7e70yAJE6qhfDFM977YyZ/B/t3YGRMxI29yOpKIiJQRn9b4hFpOxwlarn7DcP+4zLMF3KifYSK0WKuIOEuVjjjG5pyEtE1ntbpvhtwc34uMCxom+a7qnlBLre4BYlwhmJE3Y1/7C3bGBOyAEZjoWKdjiYhIGdCq8aXUthPUqgOHDmCX/oDpM9DpRCJSxalol3JhrYXDGd4t1+zWDbBnh2ef2LNVi4Qmrc6s6t6kBaZalDOhqwjTpRf2siTYnY797ivMtbc5HUlERALMpzVeq8afl3GFeO5t/+Id7KzJnq1RNVkgIg5S0S5lwhYUwK6006u6n956LfNI8QtrJp5pdW/aGho00r6o5cy4XLhG3Yz7//6M/f5b7MBRmNg4p2OJiEgA2eXzPX9p1gZTo6azYSoA03sgdsKHsHMbpG2GJi2djiQiVZiKdgkIeyIbtm880+qevhny8nwvCgnxbLXW1DOTTtNWmHj9wyEodOgOjZvBjq3YqV9grh/ndCIREQkgtcb7x8RW9+zbvnAWdvZkjIp2EXGQinbxm7UWMvb5ruq+b1fxC6NiPIV501aee9GTmmsxlyBljME16hbcrzzhaQUcOEq/UBERqSTskYOwbSMYg+nS0+k4FYZJHeYp2pfOw15/Jya2utORRKSKUtEuF2Tz8z0zsNs2YLduhG0b4Pix4hcm1j+r1b0V1L0M43KVf2C5OO06Q9NWnjUHJn+OufmXTicSEZEAsMsXeP7SvI1+IeuP5BZnutDmT8cMuc7pRCJSRalol2Ls8WPeGXS7dQPs2AoFBb4XhYZ6Zs69re6tdR90Beedbf/bI9i532EHX4upWdvpWCIiconUGn9xjDGY1KHYd/6BnTMVO+garbsjIo5Q0V7FWbfbs0f32au6Z+wtfmFs3Okt11p5Foxr3AwTFlb+gaVMmdYdoOXlsOlH7KRPMLf9xulIIiJyCezhDNi+ydMa37mX03EqHNOtL/azt+DQAVi3Ei7v6nQkEamCVLRXICEhId7/Fvx05ruUbG4upG/Bbl2P3bbRc4/byeziF9Zr6Luqe2I9bXdSRbhG3YL7L7/HLpiJHToGU7uu05FEROQieVeNb94WE1fD2TAVkImIwPQegJ0+AfesyYSoaBcRB6horwAiIyOJDg0hJDSUgox91IyNo7CggBMFheTk5Jz3sTbzsHcG3W7dALu2Q2Gh70Xh4ZDc8kyre5NWmOiYMnxHEsxM8zbQthOsW4n95mPMuPFORxIRkYtkl3mKdrXGXzyTMhQ7fQKsXY49uF+/zBaRcqeiPchVj4okIu8Ux159iZzFczwFd0gIkd1TiPvFg4RFRZJ10lO4W3ch7Nnpu6r74YziTxqf4Jk9b9YK07QNNEzGhGooyBmuUT/DvW4ldtFsz2x7vcucjiQiIn6yhw549hg3LkxnrRp/sUyd+md+mT1nKmbMHU5HEpEqRpVaEIuM9BTsGQ/8DHfWWau1FxaSs+B7ctcuJ/Gl96i2YRUnpn7puWft1E9m3o0LGjT2XdW9ZqJa3eW8THJz6HAFrF6C/eYjzN3/43QkERHxk3fV+BZqjb9UrtRhnl9mz5+OHXUzJizc6UgiUoWoaA9i0aEhHHv1Jd+C/SzurGMce/PvVB/7c06sX+U5GBEJTVpgmrX2FOrJLTGRUeUXWioN16hbcK9egl02DzvsesxlSU5HEhERP2jV+ABq3xUSasORg9il8zC9+judSESqEBXtQSokxHMPe87iOee9LmfRbGrc/yfCfvk/FCY2gMsaazsSCQjTMBnTpTd2+XzcEz8k5Nd/dDqSiIiUkj24H9K3qDU+QIwrBJMyBPvVe9jZk0FFu4iUI5fTAaRkLpcLd1Zm8UXjfqqwEPeJE4T07I9p1EQFuwSUGXkTGAMrF2F3bHU6joiIlJJ31fhWl2OqxzuapbIwfQZCSCikbdbPRBEpVyrag5Tb7cZVPR5CLlCEh4Tgqh6H2+0ul1xStZj6jTBX9AXAPeFDh9OIiEhpnVk1vrfDSSoPUz0e08Xz+bSzJjucRkSqEhXtQaqwsJDCggIiu6ec97rIHqkUFhRQeKEZeZGLZK6+CVwu+HEZdttGp+OIiMgF2Ix9sGMruFyYTmqNDyTTbxgAdskP2BPZDqcRkapCRXsQO1FQSNwvHsRVPa7E867qccTd9SAnClSwS9kxdepjenru3XNP+MDhNCIiciHe1viWl2NiS/43hFykpq3gsmTIz8POn+F0GhGpIlS0B7GcnBxyw6uR+PcPiOw94EyrfEgIkb0HkPj3D8gNjyAnJ+f8TyRyicyIGzz38W1Yjd201uk4IiJyHlo1vuwYYzD9hgJg50zB6vZEESkHKtqDXNbJHLLDIqh+35+o/8ks6r39LfU/mUX1+/5EdlgEWSdVsEvZM7XqYK4cCIB7wvtYax1OJCIiJbEZe2HndrXGlyHTPRUioyBjH2xY7XQcEakCVLRXADk5ORw6ns3h49mE1q7L4ePZHDqerRl2KVdm2FgIDYMt62HDKqfjiIhICYoWoKNVB0xsdWfDVFImohqm1wAA3LMmOZxGRKoCFe0VSNFic1p0TpxgatTEpAwBwP31B5ptFxEJQmda47VqfFkyKZ4WedYswx7OcDaMiFR6KtpFpNTM0DEQHgFpm2HNMqfjiIjIWez+PbArDUJCMJ16OB2nUjP1LoPWHcC6sT9853QcEankVLSLSKmZuBqYfsMBcE/8QAvwiIgEEe+q8a07YGLUGl/WXKmnF6SbOw2bn+9wGhGpzFS0i4hfzJBroVqkZ6GjlYucjiMiIqdp1fhy1qE7xNeE48ewKxY4nUZEKjEV7SLiFxNTHXPVSADcEz/EurXGgoiI0+y+3bA73dMa37G703GqBBMSgkkZDICdPdnhNCJSmaloFxG/mYGjICoa9u7ELp3ndBwRkSrPLj/9vbh1R0x0rLNhqhDTZxCEhMDWDdhdaU7HEZFKSkW7iPjNRMVgBo0GwE78CKsdDUREHFW01Zta48uXiU/AdOoJaLZdRMqOinYRuShmwAiIiYWMvdhFs52OIyJSZdl9u2DPDggJVWu8A0y/YQDYRbOxJ084nEZEKiMV7SJyUUy1KMyQ6wCw33yELdDKuSIiTiiaZadNR0x0jLNhqqLmbaF+I8jLxS783uk0IlIJqWgXkYtmUodD9Xg4nIGdP9PpOCIiVZJWjXeWMQaTenq2ffZkrLXOBhKRSkdFu4hcNBMRgRl2PQB20qfY/DyHE4mIVC12z07YuxNCQzEdr3A6TpVleqZCRCTs3wMb1zgdR0QqGRXtInJJTN/BUKMWHD2E/eE7p+OIiFQp3lXj23bGRKk13immWhSmZz8A3FqQTkQCTEW7iFwSExaOGT4WADv5M2xursOJRESqBmvtWavG93Y4jRS1yLNqMfbIIUeziEjloqJdRC6Z6T0AaiZCVqa2vBERKS97d8K+XZ7W+PZqjXeaadAIWrQDtxs7d5rTcUSkElHRLiKXzISGYa6+EQA79XPsqZMOJxIRqfyKFqDztMZHOxtGgDOz7Xbud9pVRUQCRkW7iASE6dEPEutD9nHszG+djiMiUqn5tsZr1fhgYTp1h7gacOwoduVip+OISCWhol1EAsKEhGBG3gSAnfYV9mS2w4lERCqxPTtg/24IDcN0UGt8sDChYZgrBwPodjERCRgV7SISMKZbH6jfCE6ewE6f4HQcEZFKy9sa364LJjLK2TDiw1w5CFwu2LwWu2eH03FEpBJQ0S4iAWNcIbhG3gyAnTERm53lcCIRkcpHq8YHN5NQCzp2B8DOnuJwGhGpDFS0i0hgdeoBDZPhVA72u6+cTiMiUvnsTocDeyAsHNOhm9NppASuogXpFs7S4qwicslUtItIQBmXC9eonwFgv/8Wm3XU4UQiIpWLtzX+8i6YamqND0qt2kPdBpCbg1042+k0IlLBhTr54uvXr2fixImkpaVx9OhRHn74Ya644sxiKosXL2bGjBls376d48eP85e//IWkpCSf58jPz+e9995j/vz55OXl0a5dO+666y5q1qxZzu9GRLzad4XkFpC2GTvlC8wNdzmdSESkUvC0xnuKdtNFrfHByhiDSR2G/fh17OzJ2NShGGOcjiUiFZSjM+25ubkkJSUxbty4c55v2bIlN9988zmf4+2332bJkiU88MADPPnkk5w6dYrnnnsOt9tdVrFF5AKMMbhG3QJ47uezRw45nEhEpJLYtR0y9nla49urNT6YmZ79ITwC9u6ELeucjiMiFZijRXunTp248cYb6d69e4nn+/bty5gxY7j88stLPH/y5Em+//57brvtNtq3b09ycjL33XcfO3fuZM2aNWUZXUQupE1HaN4GCvKxUz5zOo2ISKVwpjW+K6ZapLNh5LxMVDSmRyoAdpa2fxORi+doe/yl2r59O4WFhbRv3957LCEhgUaNGrF582Y6duxY4uPy8/PJz8/3fmyMITIy0vv3YFWULZgzSnBxcswYYzDX/IzCF/6InTsdhlyHqVWn3HOIf/R9RvylMVN+PK3xCwBwdetTYT/nVWnMuPoNp/CH77ArF8Kxo5j4BKcjVUhVacxIYFS2MVOhi/bMzExCQ0OJiYnxOR4XF0dmZuY5H/fVV1/x+eefez9OTk7m+eefp3bt2mUVNaDq1q3rdASpYBwbM/XqkTHta3JXL6HazIkkjH/UmRziN32fEX9pzJS9vK0bOXBwHyYignqDrsZVwWfaq8SYqVePA206kLd+NdGrFhJ3k9Z4uRRVYsxIQFWWMVOhi/Zzsdae9/zo0aMZMWKE9+Oi38AcPHiQgoKCMs12KYwx1K1bl/3791/wPYpAcIwZO+x6WL2EEzO/5VTqcEyd+o7kkNIJhjEjFYvGTPkpnHJ6G83Lu3LgaCaQ6WCai1fVxoy791WwfjVZkz7jxJVDMCEhTkeqcKramJFLV1HGTGhoaKkmjit00R4fH09BQQHZ2dk+s+1ZWVm0bNnynI8LCwsjLCysxHPB/EUtYq2tEDkleDg6Zpq0hMu7wo/LcH/zEa47/58zOcQv+j4j/tKYKVs+q8Z37VMpPtdVZsx06gWxb8DRw9hVi6BzL6cTVVhVZsxIwFSWMVOh92lv0qQJISEhPovOHT16lJ07d9KiRQsHk4nI2VyjPDtA2MVzsHt3OpxGRKQC2rEVDh3wrEberqvTacQPJiwMc+UgANyzpzicRkQqIkeL9lOnTpGenk56ejoAGRkZpKenc+iQZ3uo7Oxs0tPT2b17NwB79+4lPT3de796VFQU/fv357333uPHH38kLS2Nf/zjHzRq1MhncToRcZZp3Aw69QBrsRM/cjqOiEiF451l73AFJiLC4TTiL9N3MBgXbFiN3bfb6TgiUsE42h6/bds2nnjiCe/H7777LgApKSnce++9LFu2jFdffdV7/uWXXwZgzJgxjB07FoDbb7+dkJAQXnrpJfLy8mjXrh2/+93vcLkqdBOBSKXjGnkz7lWLscvnY3elYRomOx1JRKRC8LTGzwfAdOntcBq5GKZmIrTvCquXYOdMwdz4C6cjiUgF4mjR3rZtWz799NNznk9NTSU1NfW8zxEeHs64ceMYN25cgNOJSCCZy5I892EunYt7wgeE/OZ/nY4kIlIxpG+BwxkQUQ3adXE6jVwkV7/huFcvwS6YiR19KyaimtORRKSC0HS0iJQbM/ImT3vg6iXYtC1OxxERqRC8rfHtu6k1viJr3QES60HOSezi2U6nEZEKREW7iJQbU/cyTI8UANwTP3A4jYhI8PNpje/ax+E0cimMy4VJGQqAnTW5UqxoLSLlQ0W7iJQrM+JGCAmBtSuwW9c7HUdEJLilbYYjByEiEtp1djqNXCLT+yoID4fd6bBto9NxRKSCUNEuIuXKJNbD9BoAgPtrzbaLiJyPz6rx4WqNr+hMdAymW1/AM9suIlIaKtpFpNyZ4TdAaChs+hG7YbXTcUREgpJ1u7HLT7fGd9Oq8ZWF6TcMwLObSlams2FEpEJQ0S4i5c7UrI25cjAA7gkf6L4+EZGSpG2GI4egWiS0VWt8ZWEaN4PkFlBYgJ033ek4IlIBqGgXEUeYYddDWLjnnr51K5yOIyISdLyt8R27Y8LCHU4jgWRST8+2z5mKdRc6G0ZEgp6KdhFxhIlPwKR6VtF1f63ZdhGRs1m3+8yq8V3UGl/ZmG59ICbWs8jgmmVOxxGRIKeiXUQcY4ZcBxHVYMdWWL3Y6TgiIsFj+0bIPAyRUdC2k9NpJMBMWDim90AA3LO1IJ2InJ+KdhFxjKkej+k/AgD3hA+xbrfDiUREgoN3lr2DWuMrK5MyBIyBdSuxB/Y6HUdEgpiKdhFxlBk82jOTtDsdu3yB03FERBzns2p81z4Op5GyYmrXhXZdALBzpjicRkSCmYp2EXGUiY7FXDUKAPvNR1qQR0Rk20bIPAKR0dCmo9NppAy5irZ/mz8Tm5vrcBoRCVYq2kXEceaqkRAVA/t2YZf84HQcERFH+a4aH+ZwGilTbTtBrTpwMhu7VD//RKRkKtpFxHEmKhoz5FoA7MSPsAUFDicSEXGGdRd6bxUy3dQaX9kZV4jn3nbAzpqsnVREpEQq2kUkKJh+wyE2Dg7uxy783uk4IiLO2LoBjh2BqGho3cHpNFIOTO+BEBoGO7dB+han44hIEFLRLiJBwVSL9GwBB9hvP8Hm5zucSESk/Hlb4zv1wISqNb4qMLHVvV0VdtYkh9OISDBS0S4iQcOkDoW4BDhyEDtvutNxRETKlU9rfBe1xlclJvX0gnRL52GPZzkbRkSCTkCK9szMzEA8jYhUcSY8AjP8egDs5E+xeVpJV0SqkC3rISvTszBn6/ZOp5HylNwCGjeDgnzsghlOpxGRION30f7888/zySefeD8eO3YsNWvWpEGDBqxevTqg4USk6jF9BkFCLcg8gv1hqtNxRETKjVrjqy5jDCZ1KAB29hRtfyoiPvwu2v/zn//QsGFDAKZPn8706dOZMmUKQ4cO5X/+538CHlBEqhYTFoYZcSMAdvLn2NxTDicSESl7Pq3xXdUaXxWZbn09XRaHDsC6lU7HEZEg4nfRvm/fPm/R/u233zJ27FgGDRrEb3/7W5YuXRrwgCJS9Zie/aF2XTh+DPu9FuURkSpg8zo4fgyiY6GVWuOrIhMRgek9AAD3rMkOpxGRYOJ30V6jRg127doFwNSpU7nqqqsAsNZSWKhWHhG5dCY09Mxs+3dfYnNOOpxIRKRseVvjO/fEhIY6nEacYlI8LfKsXY49uN/ZMCISNPwu2q+99lpuvvlmBg4cyOHDhxk61PPNZdWqVTRr1izgAUWkajI9UqDuZXDiOHbGRKfjiIiUGVtYiF2xEADTtbfDacRJpk59aNMJrMXO0bouIuLhd9H+0ksvcd9999GmTRumT59OTEwM4Gmb//Wvfx3wgCJSNRlXCGbkTQDY6V9jTxx3OJGISBnZvNbTGh8TCy3VGl/Vufqd3v5t/nRsfp7DaUQkGPjVf5Wfn8/dd9/NI488QpMmTXzOjR8/PpC5REQwXXpjG3wKe3Zgp32NGX2r05FERALuTGt8L0xIiMNpxHHtu0JCbThyELt0HqZXf6cTiYjD/JppDwsL46uvviqrLCIiPozLhWvULQDYmd9gjx9zOJGISGB5WuNPrxrfRa3xcrrTrO9gAOxsLUgnIhfRHj969Gi+/vrrMogiIlKCjt2hcTPIPYWd+qXTaUREAmvTGsg+DjHVoeXlTqeRIGGuHAQhoZC2Gbtjq9NxRMRhfi9P2qxZM5566ikWLFhAly5diI6O9jl///33ByyciIgxBteoW3C/8gR21iTswFGY+ASnY4mIBIRdNh9Qa7z4MtXjPbeILZmDnTUZc4f+fS1SlfldtL/xxhvEx8ezfPlyli9f7nPOGKOiXUQCr11naNoKtm3ETvkcc9PdTicSEblktqAAu1KrxkvJTL+hnqJ9yQ/Y68dhomOcjiQiDvG7aE9LSyuLHCIi5+Sdbf/bI9gfpmIHj8Yk1HY6lojIpdn0o6c1PjYOWrRzOo0Em6at4bJk2J2GnT8DM+gapxOJiEP8vqe9SF5eHps2baKgoCCQeUREStaqved+z4IC7KRPnU4jInLJvKvGd1FrvBRnjMH0GwqAnTMF63Y7nEhEnOJ30X7y5EnuvPNOoqKiaNu2LTt37gQ897I/99xzAQ8oIgJnZtsB7PwZ2IP7HU4kInLxbEEBdkVRa3wfh9NIsDJXpEBkFGTsgw2rnY4jIg7xu2j/wx/+wOrVq5k9ezbVqlXzHr/qqqv45JNPAhpORORspnkbaNMJCgux3+r7jYhUYBtXw8lsqB4Pzds4nUaClKkWiek1AAD3rEkOpxERp/hdtH/99df885//pE+fPhhjvMfbtGnDtm3bAhpOROSnXNecnm1fOAu7f7fDaURELo63Nb5zL4xLrfFybibF0yLPmmXYwxnOhhERR/hdtB88eJDExMRix0+cOOFTxIuIlAWT3AI6XAHWjf3mY6fjiIj4zRbkY1cuAtQaLxdm6l3mWdfFurE/fOd0HBFxgN9Fe7du3Zg06Ux7TlGh/vrrr9OzZ8/AJRMROQfXyJsBsEvnYvfscDiNiIifNqyGkycgrgY0b+10GqkAXP2GAWDnTsPm5zucRkTKm99bvj377LMMGTKE9evXU1BQwN///nfWrVvHwoULmTNnTllkFBHxYRo1gS69YPkC3BM/JOSePzgdSUSk1Oyy+YBa48UPHbpDfAJkHsGuWIDpnuJ0IhEpR37PtPfq1Yv58+dz8uRJmjZtyrRp06hTpw4LFy6kS5cuZZFRRKQY19U3gzGwYiF2h9bTEJGKQa3xcjFMSAim7xAA7OzJDqcRkfLm90w7wOWXX84777wT6CwiIqVmGjTCdOuLXTIH94QPCLn/UacjiYhc2PpVkHMC4hKgmVrjpfTMlYOwkz6BrRuwu9IwDZOdjiQi5aRUM+1ZWVml/iMiUl7M1TeCywU/LsNu2+h0HBGRC/KuGt+1N8bld8OjVGEmPgHTybN+lGbbRaqWUv20iI+Pp0aNGqX6IyJSXkzdBpie/QBwT/zQ4TQiIudn8/OxqxYDnqJdxF+maEG6RbOxJ084nEZEykup2uNnzZrl/Xt6ejq///3vueOOO7yrxS9cuJB33nmHZ599tmxSioicgxlxI3bRHFi/Crt5LaZFO6cjiYiUbP1KyDkJ8TWhSSun00hF1Lwt1G8Ee3diF36PGXC104lEpByUqmhPSTmzQuWTTz7J3/72N2666SbvsZEjR3L55Zfz2muvcfvttwc+pYjIOZhadTB9rsLOmYp7wge4Hv6zdytKEZFg4m2N79JLrfFyUYwxmNRh2A//jZ09Gdt/hH7miVQBfv/EWLhwIV27di12vGvXrixZsiQgoURE/GGGjYXQMNi8zrP/sYhIkLH5eWe1xmvVeLl4pmcqRETC/j2wcY3TcUSkHPhdtDds2JB///vfxY7/5z//oWHDhgEJJSLiD5NQC5Pi2QrH/fX7WGsdTiQi8hPrVsCpHKhRC5q0dDqNVGCmWtSZ9Vy0IJ1IleD3lm8vvfQS1113Hd999x09evQAYNGiRWzbto0vvvgi4AFFRErDDB2DnfsdpG2GH5dB+25ORxIR8bLL5gNgumjVeLl0JnWYZwX5VYuxRw5hEmo5HUlEypDfPzWGDRvGli1bGDVqFEeOHOHw4cOMGjWKzZs3M2zYsLLIKCJyQSauBqbfcADcEz7QbLuIBA2bl4td5bmFUKvGSyCYBo2gRTtwu7FzpzkdR0TKmF8z7fn5+QwaNIj//Oc/PPPMM2WVSUTkopjB12FnT4Wd22HlQujcy+lIIiKwbiXk5kBCbbXGS8CY1GHYzWuxc7/DDr8eExrmdCQRKSN+zbSHhYWxdu1arVIpIkHJxFbHXOXZ/sY94UOsu9DhRCIiZ60a37W3/g0lAWM6dYe4GnDsKHblYqfjiEgZ8rs9/rbbbuO///1vWWQREblkZuA1EBnt2cN26Tyn44hIFWfzcrGri1rjtWq8BI4JDcNcORjAc3+7iFRafi9El5eXxxtvvMH06dPp2rUr0dHRPuf/9re/BSyciIi/THQMZtA12AkfYL/5GNu1DyYkxOlYIlJVrV0OuaegZiIkNXc6jVQy5spB2Mmfwua12D07MA0aOx1JRMqA30X72rVr6dy5MwCbN2/2OaeWLxEJBuaqq7EzJ8KBPdjFszG9BjgdSUSqKJ9V4/XvJAkwk1ALOnaHFQuxs6dgbvmV05FEpAz4XbTPmjWrLHKIiASMqRaFGXwt9ot3PLPtV6RgQv3+dicicklsrlrjpey5UofhXrEQu3AW9rrbMNWinI4kIgF2URuFZmZmsmzZMpYvX05mZmaAI4mIXDrTbzhUj4dDB7ALZjgdR0SqorXLIC/3dGt8M6fTSGXVqj3UbQC5OdiFs51OIyJlwK+iPT09neHDh1OrVi26d+/OFVdcQa1atRgxYgTp6ellFFFExH8mohpm6BgA7LefYvPzHE4kIlWNtzW+ax+1xkuZMcZgUocBngXprLXOBhKRgCt10b5r1y569OjBmjVreOqpp/jiiy/4/PPPefLJJ1m9ejU9e/Zk9+7dZZlVRMQvJmUIxNeEo4ewP0xzOo6IVCE29xR2zVIATDe1xkvZMj37Q3gE7N0JW9Y5HUdEAqzURftjjz1Gy5Yt2bJlC3/4wx+45pprGD16NH/84x/ZvHkzLVq04LHHHivLrCIifjFh4ZjhYwGwUz7D5uY6nEhEqowfT7fG164LjZo6nUYqORMVjemRCoCdpe3fRCqbUhftU6dO5ZlnnqFatWrFzkVGRvLUU08xZcqUgIYTEblUps9VnvtJjx3FztE/ZESkfLiXzQPAdNWq8VI+vC3yKxdiM484G0ZEAqrURfvhw4dJSko65/kmTZpw+PDhQGQSEQkYExqGufpGAOyUL7CnTjqcSEQqO3sqxzPTjlaNl/JjGiZDs9ZQWIidp1vCRCqTUhft9evXZ926c98js3btWurVqxeQUCIigWR69IPE+pCdhZ35rdNxRKSSsz8ug7w8SKwHDZs4HUeqEO9s+5zvsIWFzoYRkYApddE+atQo/ud//oeDBw8WO5eRkcHvfvc7rrnmmkBmExEJCBMScma2fdpX2JPZDicSkcrMFrXGd1FrvJQv07kXxMZB5mFYvdjpOCISIH4tRHfq1CmaNm3Kr3/9a1555RVeeeUVfvWrX9GsWTNycnJ49NFHyzKriMhFM1dcCfUawskT2OkTnY4jIpWUPXUSflwOqDVeyp8JC8NcOQgA92ytNSVSWZS6aK9RowaLFy/mlltu4eOPP2b8+PGMHz+eTz/9lJtvvpmFCxeSkJBQlllFRC6acYXgGnUzAHbGBGx2lsOJRKQysquXQn6e55achslOx5EqyPQdDMYFG1Zj92k7ZpHKoNRFO3gK93/9618cPnyY/fv3s3//fg4fPsy///1vatasWVYZRUQCo1NPuCwZTuVgp33ldBoRqYTs8vmAZ5ZdrfHiBFMzEdp3BcDO0Wy7SGXgV9FexBhDYmIiiYmJ+oEkIhWGcblwXXMLAHbmt9isow4nEpHKxKc1vltvh9NIVebqNxwAu2AmNveUw2lE5FJdVNEuIlJhte8GyS0gLxc75Uun04hIJWJXL4WCfKjbABokOR1HqrLWHTy7F+ScxC6e7XQaEblEKtpFpEoxxuAaefre9tmTsUcPO5xIRCoL76rxao0XhxmXC5MyFAA7azLWWocTicilUNEuIlVP207QrA0U5GMnf+Z0GhGpBGzOSVirVeMleJjeV0F4OOxOh20bnY4jIpdARbuIVDnGmDP3ts+dhj2c4XAiEano7OrFUFAAdS+D+o2cjiOCiY7BdOsLeGbbRaTiCi3NRa+88kqpn/D++++/6DAiIuXFtLzcc8/fhtXYbz/B3H6f05FEpAKzy7RqvAQf028Ydv4M7PL52BvuxFSPdzqSiFyEUhXtL730UqmezBjjV9G+fv16Jk6cSFpaGkePHuXhhx/miiuu8J631vLZZ58xc+ZMsrOzad68OXfeeScNGzb0XvP444+zfv16n+ft1asX48ePL3UOEamaXKNuwb1htWd13aHXYRLrOx1JRCoge/IErFsBqDVegotp3Myz+GraZuy86Zhh1zsdSUQuQqmK9rS0tDJ58dzcXJKSkujXrx8vvvhisfMTJkxg0qRJ/PrXv6ZevXp8+eWXPP3007z88stERkZ6rxswYAA33HCD9+Pw8PAyySsilYtp2gradYG1y7HffIK580GnI4lIBWRXL/G0xtdriGmg1ngJLiZ1GDZtM3bOVOyQazGuEKcjiYifHL2nvVOnTtx4441079692DlrLZMnT2b06NF0796dRo0ace+995Kbm8u8efN8ro2IiCA+Pt77JyoqqrzegohUcN572xfPxu7b5XAaEamIzl41XiTYmG59ICYWjhyENcucjiMiF6FUM+0/tXv3biZOnMjOnTvJy8vzOfe3v/0tIMEyMjLIzMykQ4cO3mNhYWG0adOGTZs2MXDgQO/xuXPnMnfuXOLi4ujYsSPXX3+9z0z8T+Xn55Ofn+/92BjjvT6Y70MryhbMGSW4aMxcmElqju3UA7tyEXbiR7h+9TunIzlKY0b8VdXHjD2ZDetWAuDqpvvZS6Oqj5nyZsIjsH0GYad+gZ09BVenHk5H8pvGjPirso0Zv4v2mTNnMnLkSJKTk9m0aRPt2rUjPT0day2dO3cOWLDMzEwA4uLifI7HxcVx6NAh78d9+vQhMTGR+Ph4du3axYcffsiOHTt45JFHzvncX331FZ9//rn34+TkZJ5//nlq164dsPxlqW7duk5HkApGY+b88u58gAO/WYRdNo+ap+4lPLm505EcpzEj/qqqY+bEjG85UlhAWOOm1O1SvHNQzq2qjhknFIy5lX3ffYldt4Ja7nzCKuhtHBoz4q/KMmb8Ltr/8Ic/8NBDD/Hkk08SGxvLF198QWJiIrfccgtDhgwJeMCf/nbEWuvz8VVXXeX9e6NGjahXrx6///3v2b59O02aNCnxOUePHs2IESOKvcbBgwcpKCgIVPSAM8ZQt25d9u/fX+zzIFISjZlSqhaD6XYldulcMt54mZDf/K/TiRyjMSP+qupjpnDGt57/duzBvn37HE5TMVT1MeOMEEy7Ltgfl3Hgs3cJueFOpwP5RWNG/FVRxkxoaGipJo79Lto3bNjARx995H2RnJwcYmJiePLJJxk1ahT33HOP/2lLEB8fD3hm3GvUqOE9npWVVWz2/WzJycmEhISwf//+cxbtYWFhhIWFlXgumL+oRay1FSKnBA+NmQszV9+EXTYfu2ox7rTNmKSqPduuMSP+qopjxp7Ixq73tMbTpXeVe/+XqiqOGSeZfsOwPy7Dzp+Be9QtmIgIpyP5TWNG/FVZxozfC9FFR0eTm5sLQP369dm2bZv33Nlt65eqqOV9zZo13mMFBQWsX7+eli1bnvNxu3btorCw0Fv0i4iUhql3GaZ7CgDuCR86nEZEKgK7ahEUFkKDxph6lzkdR+T82naCWnXgZDZ26Q9OpxERP/g9096jRw/mz59PmzZtGD58OA899BA//vgjX375JT16+LewxalTp9i/f7/344yMDNLT04mJiaFWrVoMGzaMr776inr16lG3bl2++uorIiIi6NPHszrr/v37mTdvHp06dSI2Npbdu3fz3nvvkZycTKtWrfx9ayJSxZmrb8QumePZAm7rBkyz1k5HEpEgplXjpSIxrhBMyhDsF+9gZ03G9r6q0izSJVLZ+V20/+1vfyM7OxuAxx9/nOzsbD755BOaNWvGSy+95Ndzbdu2jSeeeML78bvvvgtASkoK9957L6NGjSIvL4833niDEydO0KxZM/70pz95V3oPDQ3lxx9/ZPLkyZw6dYqaNWvSuXNnrr/+elwuR3ezE5EKyCTWw/S+Cjt3Gu4JHxDy0NNORxKRIGVPHIcNqwEwXXs7nEakdEzvgdgJH8LObZC+BZJbOB1JRErB76L97PvEo6KiePXVVy/6xdu2bcunn356zvPGGMaOHcvYsWNLPF+rVi2fol9E5FKZ4WOxC76HjWuwG9dgWrV3OpKIBCG78nRr/GXJmLpqjZeKwcRWx3Trg104CztrEkZFu0iF4Pd0dJMmTTh8+HCx45mZmedc+E1EpKIwNRMxfQcB4J7wQaVYvEREAu9Ma7xm2aViManDALBL52GPZzkbRkRKxe+iPT09ncLCwmLHc3Nz2bNnT0BCiYg4yQy7HsLCYesGWLfS6TgiEmRsdtZZrfG6n10qmOQW0LgZFORjF8xwOo2IlEKp2+MnTpzo/ft3333ns+1aYWEhM2fOJCkpKaDhREScYOJrYlKHYqdPwP31+7jadtJiPSLiZVcuArcbGjXB1KnvdBwRvxhjMKlDse/8Azt7CnbgKIwrxOlYInIepS7ar7nmGsDzP/rtt9/ucy4sLIykpCRefPHFgIYTEXGKGXId9ofvYMdWWL0EOnZ3OpKIBAmtGi8VnenWF/vZW3DogKej7PKuTkcSkfModXu82+3G7XbTqFEjMjIyvB+73W5yc3PZtGkTI0aMKMusIiLlxlSPx/QfDnj2bbdut8OJRCQY2OPHYOMaAEwX3c8uFZOJiMD0HgCAe9Zkh9OIyIX4fU97WloatWrVKossIiJBxQy+FiKjYHcarFjgdBwRCQJ25cLTrfFNMYn1nI4jctFMylDPX9Yuxx7c72wYETmvi9rMfM6cOVx99dU0a9aM5s2bM3LkSObOnRvobCIijjLRsZirRgLgnvgR1l18EU4RqVrssvmAWuOl4jN16kObTmAtds5Up+OIyHn4XbS///77XHXVVURFRXH//ffzm9/8hsjISAYMGMCHH35YFhlFRBxjrhoFUTGwbxd2iX45KVKV2axM2PgjoK3epHJw9Tu9/dv86dj8PIfTiMi5+F20P/PMM/zlL3/hk08+4f777+eBBx7gk08+4bnnnuOpp54qi4wiIo4xUdGYwaMBsN98hC1hy0sRqRrsykVg3dC4GaZ2XafjiFy69l0hoTZkH8cuned0GhE5B7+L9u3bt3P11VcXOz5y5EjS0tICEkpEJJiY/iMgNg4y9mEXfu90HBFxiHfV+G5qjZfKwbhCMH0HA2Bna0E6kWDld9HesGFDZs6cWez4zJkzadiwYUBCiYgEE1MtEjPkWgDst59gC/IdTiQi5c1mHYVNawGtGi+Vi7lyEISEQtpm7I6tTscRkRKUumgfN24cx48f56GHHuL+++/nnnvu4b333uP999/nV7/6FQ888AAPP/xwWWYVEXGMSRkGcQlwOAM7b7rTcUSknNkVCz2t8cktMLXqOB1HJGBM9XjvL6Kstn8TCUqlLtrfeecdcnJyuOeee/j444/58ccfGT9+PA888ABr167lk08+4Ze//GVZZhURcYyJiMAMGwOAnfQpNi/X4UQiUp7OrBqvWXapfEw/z/ZvdskP2BPZDqcRkZ8KLe2F1lrv30ePHs3o0aPLJJCISLAyVw7GfvclHDmE/WGqZ2V5Ean07LGjsFmt8VKJNW0NlyXD7jTsgpmYgfr5JhJM/Lqn3RhTVjlERIKeCQvDDL8BADv5c2zuKYcTiUh5sCsWgLWe1viaiU7HEQk4Y8yZ2fbZk7Fut8OJRORsfhXtLVq0ICEh4bx/REQqM9NrANSuC8ePYWdNcjqOiJQD76rxXbVqvFRe5ooUiIyCjH2wYbXTcUTkLKVujwd44okniIuLK6ssIiJBz4SGYkbciH3rZezUL7EpQzGRUU7HEpEyYjOPwJb1gFrjpXIz1SIxvQZgZ36De/ZkQtp2cjqSiJzmV9F+4403kpiotjARqdpMjxTslM9g/x7szImYETc6HUlEyoi3Nb5pK0zN2k7HESlTJmUoduY3sHop9vBBjXmRIFHq9njdzy4i4mFcIZirbwLATpuglXZFKrEzrfGaZZfKz9S7DFq1B+vG/jDV6Tgiclqpi/azV48XEanqTNc+0KAx5JzATvva6TgiUgbs0cOwdQMAprOKdqkaXP2GAWDnTsPm5zucRkTAj6Ld7XarNV5E5DTjcuEaeTMAduY32ONZDicSkUDztsY3a41JqOV0HJHy0aE7xCd4FlxdscDpNCKCn6vHi4jIWTr1gEZNITcH+90XTqcRkQDTqvFSFZmQEEzfIYBn+zcRcZ6KdhGRi2SMwXXNLQDYWZOwx446nEhEAsUeOXRWa3wvh9OIlC9z5SAICYGtG7C70pyOI1LlqWgXEbkU7bpAk5aQl4ed8rnTaUQkQOyK+Z6/NGuDqVHT2TAi5czEJ2A69QQ02y4SDFS0i4hcAmMMrlGnZ9vnTMEeOehwIhEJBLvMU7SrNV6qKpN6ekG6RbOxJ084G0akilPRLiJyqVp3gBbtoKAAO+kzp9OIyCWyRw7Cto1gDKZLT6fjiDijRVuo3wjycrELZzmdRqRKU9EuInKJfGbb50/HHtzvcCIRuRR2+ekVs5u3wcSrNV6qJmMM3tn22ZO1/bOIg1S0i4gEgGnRFtp0hMJC7LefOB1HRC6BVo0X8TA9UiEiEvbvho1rnI4jUmWpaBcRCRDvbPvCWdj9exxOIyIXwx7OgO2bPK3xWjVeqjgTGYXp2Q8A9+wpDqcRqbpUtIuIBIhp0hLadwPrxn7zsdNxROQi2OWnV41v0Q4TV8PZMCJBwKQO9fxl1SLPVogiUu5UtIuIBJBr1M0A2KU/YPfscDiNiPjrzKrxvR1OIhIcTIPGnkXp3G7s3GlOxxGpklS0i4gEkGnUFDr3AmtxT/zI6Tgi4gd76ACkbQbjwnTWqvEiRUzqcADs3O+wBQXOhhGpglS0i4gEmGvkzWAMrFiA3bnN6TgiUkpnWuPbYqqrNV6kiOnUHeJqwLGj2JWLnI4jUuWoaBcRCTDToBGmW18A3BM+dDiNiJSWXapV40VKYkLDMFcOAjzbv4lI+VLRLiJSBszVN4JxwZql2O2bnI4jIhdgD+6HHVvVGi9yDubKweBywea12D07nY4jUqWoaBcRKQOmboMz2+Rotl0k6Hlb41tdjqke72gWkWBkEmpBx+6AZttFypuKdhGRMmJG3AAhIbB+JXbzOqfjiMh5aNV4kQtzpQ4DwC6chT110uE0IlWHinYRkTJiatfF9B4IgHvCB1hrHU4kIiWxGfs8rfEuF6aTWuNFzqlVe6jbAHJzsItmO51GpMpQ0S4iUobM8OshNBQ2r4WNa5yOIyIlONMa3x4TG+dsGJEgZozBFM22z5qsX0aLlBMV7SIiZcgk1MakDAXA/fX7+geOSBCyy7RqvEhpmZ79ITwC9u6ELbr1S6Q8qGgXESljZugYCA+H7Ztg7XKn44jIWeyBvbBzu6c1vmMPp+OIBD0TFY3pkQqAnT3F2TAiVYSKdhGRMmbiamBShwPg/lr3tosEk6JZdlp1wMRWdzaMSAXhbZFfsQCbecTZMCJVgIp2EZFyYIZcCxGRsHMbrFzkdBwROU2rxov4zzRMhmatobAQO2+a03FEKj0V7SIi5cDExmEGXA2Ae+KHWLfb4UQiYvfvgd1pEBKC6aTWeBF/eGfb53yHLSx0NoxIJaeiXUSknJhB10BkNOzZcaYlV0Qc4101vnUHTIxa40X8YTr3gtg4yDwMqxc7HUekUlPRLiJSTkx0DGbQKADsNx9pZkLEYVo1XuTimbAwzJWDAHBrQTqRMqWiXUSkHJkBIyE6FvbvwS6e43QckSrL7tsNu9MhJFSrxotcJNN3MBgXbFjt+X9KRMqEinYRkXJkIqM8i9IB9tuPsQUFDicSqZrs8tO3qLTpiImOcTaMSAVlaiZC+64A2DmabRcpKyraRUTKmek33HMf4MH92AUznY4jUiVp1XiRwHD182xpahfMxOaecjiNSOWkol1EpJyZiGqYYWMAsJM+webnO5xIpGqxe3fCnh2nW+O7Ox1HpGJr3QES60HOSd32JVJGVLSLiDjApAyF+Jpw5BB27ndOxxGpUopm2WnTEROl1niRS2FcLs/PNMDOmoy11uFEIpWPinYREQeYsHDM8OsBsJM/x+blOpxIpOrQqvEigWV6XwXh4bA7DbZtdDqOSKWjol1ExCGmz0ComQjHjmC1XY5IubB7dsK+XRAaiul4hdNxRCoFEx2D6dYXADt7ssNpRCofFe0iIg4xoWGYETcAYKd8jj2V43AikcrPu2p8285qjRcJINNvGAB2+XxsVqazYUQqGRXtIiIOMj37exbwyc7Cfv+t03FEKjVrrVaNFykjpnEzSG4BBQXYedOdjiNSqahoFxFxkAkJwVx9IwD2u6+wJ084nEikEttb1BofhumgVeNFAs2knp5tnzMV6y50NoxIJaKiXUTEYeaKvlCvIZzMxs6Y4HQckUqraAE62nXGREY5G0akEjLd+kBMLBw5CGuWOR1HpNJQ0S4i4jDjCsE18iYA7IyJ2OwshxOJVD6e1nitGi9SlkxYOKb3QADcWpBOJGBUtIuIBIPOveCyZMg5iZ32ldNpRCqfPemwf8/p1vhuTqcRqbRMyhAwBtatxGbsdTqOSKWgol1EJAgYlwvXqJsBsDO/1cq7IgFml3oWoKNdF0w1tcaLlBVTuy606wKg7UxFAkRFu4hIsOhwBSQ1h7xc7NQvnE4jUmn4tsZr1XiRsuYq2v5t/kxsbq7DaUQqPhXtIiJBwhiDa9QtgGd2wmYedjiRSCWxOx0y9kJYuFrjRcpD205Qq45ngdVlc51OI1LhqWgXEQkmbTtBs9aQn4ed/JnTaUQqBe+q8ZerNV6kPBhXiOfedsDOmoy11uFEIhWbinYRkSDiM9v+wzTs4QyHE4lUbFo1XsQZpvdACA2DHVshfYvTcUQqNBXtIiJBxrRqD63aQ2EBdtKnTscRqdh2bYeMfRAejrm8q9NpRKoME1vds287ntl2Ebl4KtpFRIKQd7Z9/gxsxj6H04hUXGda47tiqkU6G0akijGppxekWzoXezzL2TAiFZiKdhGRIGSatYZ2ncHtxn77sdNxRCokT2u8Z6s300Wt8SLlLrkFNG4GBfnYBTOcTiNSYaloFxEJUt7Z9kVzsPt2O5xGpALauQ0O7ve0xrdXa7xIeTPGYFKHAqd3RXG7nQ0kUkGpaBcRCVImqTl07A7Wjf3mI6fjiFQ4dunpBegu74aJqOZwGpGqyXTrC1ExcOgArFvhdBypIkJCQnz+W9GpaBcRCWKuUTcDp+8H3J3mcBqRisNn1fhuao0XcYqJiMD0HgCAWwvSSRmLjIykVmwMNWNjKMjYR83YGGrFxhAZWbHXNAl18sXXr1/PxIkTSUtL4+jRozz88MNcccUV3vPWWj777DNmzpxJdnY2zZs3584776Rhw4bea/Lz83nvvfeYP38+eXl5tGvXjrvuuouaNWs68ZZERALKXJaM6doHu2we7gkfEXLvH52OJFIx7NgKhzMgPALaqTVexEkmZSh2+gRYuxx7cD+mdl2nI0klVD0qkoi8Uxx79SVyFs+BwkIICSGyewpxv3iQsKhIsk7mOB3zojg6056bm0tSUhLjxo0r8fyECROYNGkS48aN49lnnyU+Pp6nn36anJwzn+y3336bJUuW8MADD/Dkk09y6tQpnnvuOdy6Z0ZEKgkz8iYwLli1CLtjq9NxRCoE7yx7hyswEREOpxGp2kyd+tCmE1iLnTPV6ThSCUVGegr2jAd+Rs6C7z0FO0BhITkLvifjgZ8RkZdbYWfcHS3aO3XqxI033kj37t2LnbPWMnnyZEaPHk337t1p1KgR9957L7m5ucyb5/lBfPLkSb7//ntuu+022rdvT3JyMvfddx87d+5kzZo15f12RETKhKnXENM9BQD31x84nEYk+PmsGt+1t8NpRATA1e/09m/zp2Pz8xxOI5VNdGgIx15/CXfWsRLPu7OOceyNl4gOrZj3uDvaHn8+GRkZZGZm0qFDB++xsLAw2rRpw6ZNmxg4cCDbt2+nsLCQ9u3be69JSEigUaNGbN68mY4dO5b43Pn5+eTn53s/NsZ4f+tijCmbNxQARdmCOaMEF42ZysN19Y0ULpkDa5fD9k2Ypq3K5HU0ZsRfQTlm0rZ4WuMjqmEu7xpc2SQ4x4yUvQ7dIKE2HDkIy+djevYv9UM1ZuRcbO4pXPv3ENKug6cl/jxyFs2mxoOPERoaSmHRTHwFEbRFe2ZmJgBxcXE+x+Pi4jh06JD3mtDQUGJiYopdU/T4knz11Vd8/vnn3o+Tk5N5/vnnqV27dmDCl7G6dXUfkPhHY6YSqFePI1ddzYlpEwid/BmJf361TF9OY0b8FUxjJnPSJxwHonqkULNxktNx5ByCacxI+cgacT3H3n2V0HnTqXPtLX4/XmNGCg8fJHf9anI3rCZvw2rytm0ipFkr3HUfPdMSf84HF2Kzs0hMrHjjKGiL9iI//Y2atfaCj7nQNaNHj2bEiBHFXuPgwYMUFBRcRMryYYyhbt267N+/v1SfBxGNmcrFDhgJMyeRu3oJe2ZNw9Xq8oC/hsaM+CvYxoy1lsLT98yeatuFffv2OZxIfirYxoyUH9uxJ3zwGnmb1rJ34VxMUrNSPU5jpmqy7kLYvQO7bQN2q+cPhzOKXec2Lly1akNIyPkL95AQTEx1MjIygmamPTQ0tFQTx0FbtMfHxwOe2fQaNWp4j2dlZXln3+Pj4ykoKCA7O9tntj0rK4uWLVue87nDwsIICwsr8VxF+EZgra0QOSV4aMxUEgm1MVcOws6ejPvr9+G3z5ZZq6DGjPgrWMaM3bYRjhyCiEho2ykoMknJgmXMSDmKjcN06Y1dMgf3rEm47rjfr4drzFRu9tRJ2L4Ju3UjdtsG2L4JTv1ktXfjgssaY5q1hqatMc1a406oTaGFyO4pnkXoziGyRyqFBQVBPUl7LkFbtCcmJhIfH8+aNWtITk4GoKCggPXr13PLLZ52miZNmhASEsKaNWvo1asXAEePHmXnzp3ea0REKhMz7HrsvOmwdT2sXwVtOzkdSSSoeBeg63AFJlyrxosEG9NvKHbJHOySH7DXj8NEx1z4QVLpWGvhyEHP7PnWDZ4iffcOsD/ZAaxaJDRpiTldoNOkBaZaVLHnO1FQSNwvHiR37fISF6NzVY8j7q4HyS4Ijhl2fzlatJ86dYr9+/d7P87IyCA9PZ2YmBhq1arFsGHD+Oqrr6hXrx5169blq6++IiIigj59+gAQFRVF//79ee+994iNjSUmJob33nuPRo0a+SxOJyJSWZgaNTGpw7AzJuD++n1cbTpqYR6R06zbjV1xumjvplXjRYJS09ZwWTLsTsMumIkZOMrpRFIObEEB7ErzFOdFRXrmkeIX1kz0mUWnQSOM68Irvufk5BAWFUni3z/g2BsvkbNo9pl92nukEnfXg+SGR5BTQfdpd7Ro37ZtG0888YT343fffReAlJQU7r33XkaNGkVeXh5vvPEGJ06coFmzZvzpT3/y2V/v9ttvJyQkhJdeeom8vDzatWvH7373O1wuR3ezExEpM2boddgfpkL6FlizFDpc4XQkkeCQttnTGl8tEtp2djqNiJTAGOOZbX/vVezsydgBV2P07/ZKx57Ihu0bPfeib9vo+f6cl+t7UUgINGyCadbasytOs9aY+JoX/ZpZJ3OIjIyk+n1/osaDj2GzszAx1SksKCC7oLDCFuzgcNHetm1bPv3003OeN8YwduxYxo4de85rwsPDGTduHOPGjSuLiCIiQcdUj8f0H4Gd+gXuCR/guryr/sEjAthl8wAwHbtjwsIdTiMi52KuSMF+/jZk7IMNq3WrVwVnrYWD+85qdd8Ie3cWvzAq2jOD3rQVplkbSGqOiQjsbUw5OTnk4FngLTGxLhkZGRXyHvafCtp72kVE5NzM4NHY2ZNhVxqsXAhd1AosVZt1u8/cz961j8NpROR8TLVITK8B2Jnf4J49mRAV7RWKzc+HHVux2zwz6WzbAMeL30dOYv0zM+jNWkPdy8ptkqFodfhgWSX+UqloFxGpgExMdcxVo7Dffox7woe4OvUo1T1fIpXW9o2QeRgio6CNCgCRYGdShmJnfgOrl2IPH8TUvPC2V+IMe/wYbNtwZlX39K1QkO97UWgoNG52utW9NTRthake70jeykhFu4hIBWUGjsR+/w3s24VdOg/TPcXpSCKO8c6yd+yOOce2riISPEy9y6BVe9i4BvvDVMzoW52OJHi6ljiwx7fV/cCe4hfGxnkK86IivXFT3ZZUhlS0i4hUUCYqBjNoNPbr97ETP8J27YMJ0Wy7VD0+rfFd1BovUlG4+g3DvXENdu407Igb9Qs3B9jcXNixxbNg3NbTe6OfOF78wnoNfVd1T6yn3WvKkYp2EZEKzAy4GjtjImTsxS6ahel9ldORRMrf1g1w7AhERkObjk6nEZHS6tAd4hMg8wh2xQJ1jJUDm3nEt9V95zbP1mhnCw+HpBZnVnVv2goTHetMYAFUtIuIVGimWqRnC7jP3sJ+8zG2ewomVDMVUrX4rhqv8S9SUZiQEEzfIdiJH3oWV1XRHlDWXQh7d/q2uh86UPzCuARoVtTq3gYaJmNCVSYGE301REQqOJMyDDvtazicgZ03A5M61OlIIuXGuguxKxYCYLqpNV6kojFXDsJO+sRTVO5KwzRMdjpShWVPnYTtm8+s6p62CXJO+l5kDDRIOt3q7inUqZmoVvcgp6JdRKSCMxERmKHXYz9+DTvpU2zvAVoMRqqOotb4qGho3cHpNCLiJxOfgOnUE7tsHnb2ZMyt9zodqcKwhw9it66Hbadb3Xelg3X7XhQRCU1anFkwrklLTGSUI3nl4qloFxGpBEzfwdhpX8KRQ9g5UzFXjXQ6kki58LbGd+qhW0NEKiiTOsxTtC+ajb3uDkxUtNORgo4tLITdab6t7kcPFb+wZuKZvdGbtoYGjbVIbSWgol1EpBIwYWGY4WOx772KnfI59srBmIgIp2OJlCnrLsQuXwCA6arWeJEKq0VbqN/Ic//1wlmYASOcTuQ4ezIbtm86s6p72mbIy/W9yOWChk3OrOretBUmoZYzgaVMqWgXEakkTK+rsFO+gEMHsLMnYQZf63QkkbK1ZT1kZUJUDLRSa7xIRWWMwaQOw374b+zsydj+w6vUPdbWWji431OcF7W6790J1vpeGBUNTVqdWdU9uQUmopozoaVcqWgXEakkTGgo5uobsW/9HTv1C2zKEEw13bcmlZe3Nb5zT610LFLBmR6p2C/egf27YeOaSr1Ghc3Ph53bsNs2eAt1sjKLX5hY76xW9zZQ7zKMy1XuecV5+gknIlKJmO6p2Mmfw4E92BnfYEbc4HQkkTJhC89qje/S2+E0InKpTGQUpmc/7OzJuGdPIaQSFe32eBZs33im1T19CxTk+14UGgqNm2FOt7nTrBWmeg1nAkvQUdEuIlKJmJAQz2z7Gy9ip32N7TccEx3jdCyRwNu8Fo4fg+hYaNXe6TQiEgAmdahnv/ZVi7BHDlXI+7OttbB/j++q7vv3FL8wprp3yzXTtDUkNdPOL3JOKtpFRCoZ0+1K7JTPYc8O7PSvMdf8zOlIIgFnl80H1BovUpmYBo09i9JtXoedOw0z6manI12QzcuF9K2+re4njhe/sF5D31Xd69SvUvfty6XRTzkRkUrGuFy4Rt6E+1/PYWd8gx0wEhNb3elYIgFjCwuxKxcCYLqqNV6kMjGpw7Gb12HnfocdPjbofilnjx2F0wW63boBdm6HwgLfi8LCIbm5ZzX3pm2gaUtMjH4Oy8ULrv8LREQkMDr1hEZNYOd27HdfYsbc4XQikcApao2PiYWWao0XqUxMp+7YuBpw7Ch25SJMN+e2c7Rut2cburNXdT+4v/iFcTU8W64VrereqAkmNKz8A0ulpaJdRKQSMsbgGnUL7n88hZ31LXbgKEycFrSRyuHMqvG9MCEhDqcRkUAyoWGYKwdhv/3Ec3/7/2/vvsOjKtP/j7/PTCqkkkoISC9JaAGkCYQaG1JUBAUMWCiC6M+vsuq66rqu4qosKoJYEOmw0hQFVEIRlBZa6FUEpAQlITAJmZnz+yNmNIYWBWaSfF7XxWUyc8o9k8cz557nPve5jkm7mWODA7vzS9337YR9u8B29g8BGlDphsKl7uFRKnWXa0pJu4hIaVW/KVSrnX8C8uX/MHo/5O6IRP4y0+HATPu1a3xT983Aici1Y7RJxvxiNuxOxzxyCCP2hmuyH/Pnk/nJeUGp++ED4HQWXsjXD6rX+a2re/U6GOXKX5N4RC5GSbuISCllGAaW7n1xjv4H5vJFmF16lMhOvCKF7NoC2WcgMBhqJ7g7GhG5BowK4dCoOaR9h7nsC6z3DwPAarVit9svs/aFmQ4HHD74a6n7jvxS958zii5YITx/9rxgFj22qip6xO2UtIuIlGb1Gv7WifeLWRh9h7o7IpG/xNU1vnFLnUiLlGKWpFvxC6lAYPd7sQaUx37iJ8ICg3HY7Zy1O7DZbJdc3zx3Fvbv+q2r+4HdkJvzh51YoHL135W618WoEHENX5XIn6OkXUSkFHNd2/6fZzC//RozuSdGRLS7wxL5U0y7HTNNXeNFyoLgJi3wrRtH5sdjsa1ZDg4HWK34N29H8EOP413On6xz+Ym7aZqQcTx/9ryg1P3oITDNwhv1L5/fyb1G3fxZ9Gq1Mfz83fDqRIpHSbuISCln1E6AuEawfRPmwpkYKSPcHZLIn7NzS/79j1UaL1Kq+fv743s+hxP/NxBnVuZvTzgc2FYvJTd9A5H/nYzf3u2c/WoB7NsBmb8U3VBE9O9K3etCTBUMi+X6vRCRq0RJu4hIGWDpdh/O7Zswv0vFvOVujKgYd4ckUmyurvFN1DVepDQr72Ul893RhRP233FmZZL54RiCeg3g7K+NKbF6wQ018mfRa9bLvwWb7poipYSSdhGRMsCoXie/m/zW9ZifTcd48Al3hyRSLKbdjrnxe0Bd40VKM6vVitXLK78k/hJs3y8jdPizeKc8iiOiIlStieHje52iFLm+VB8iIlJGWLrdB4C5dgXmkUNujkakmHZuhnPZEBQCteLcHY2IXCMWiwVn1un8a9gvxeHAee4s1qRbMGrHK2GXUk1Ju4hIGWHcUAMSW4Jp4vxsmrvDESmWQqXxFpXGi5RWTqcTS1AIXO4SGKsVS1Awzj/eV12kFFLSLiJShljuuBcMAzasxjy0393hiFwR056n0niRMsLhcOCw2/Fv3u6Sy/m3SMJht+O43Iy8SCmgpF1EpAwxKt2A0awNAM4Fmm2XEmLHZjh3FoIrQM167o5GRK6xs3YHwQ89jiUo+ILPW4KCCX7wcc7albBL2aCkXUSkjDG69gbDApvXYh7Y7e5wRC7LXPdraXxiS5XGi5QBNpuNXB8/IsdMxb91x99K5a1W/Ft3JHLMVHJ9fLHZbO4NVOQ6Ufd4EZEyxoiOxWiRhPndUpzzp2J97EV3hyRyUWZeHuamNYBK40XKkqxzNvz9/Qka/iyhjz+PmZ2FERCEw24n2+7Adk4Ju5QdmmkXESmDjK6982cutm3E3LPd3eGIXNz2TWBTabxIWWSz2cg4k82pM9l4RURz6kw2GWeyNcMuZY6SdhGRMsiIiMZo3QkA5/ypbo5G5OJcXeObtsaw6LRFpCwqaDanpnNSVunTT0SkjDJu6wVeXrBrK+aOze4OR6QIMy8Pc3NBaXxrN0cjIiLiHkraRUTKKKNCBEbbm4H82XbTNN0ckcgfbN8ItnMQEgbV67o7GhEREbdQ0i4iUoYZt9wF3j6wbyekp2H9tUNvwX9F3Eml8SIiIuoeLyJSphkhFTDa34a//TyBdeOwBgZgP/ETYYHBOOx2ztodavgjbmHmnVfXeBEREZS0i4iUeSH3Pohvbg6Zk8ZiW7McHI78e+E2b0fwQ4/jXc6fLN1aR663bWmQY4MK4VCttrujERERcRvVmomIlGH+/v74mk5OPDkQ2+ql+Qk7gMOBbfVSTozoi+/5XPz9/d0bqJQ55rpVABiJKo0XEZGyTZ+CIiJlWHkvK5nvj8aZlXnB551ZmWR+MJryXrrGXa4f83wu5ua1gLrGi4iIKGkXESmjrFYrVi+v/JL4S7B9vwyrl5ea08n1k54GuTaoEAHV67g7GhEREbdS0i4iUkZZLBacWad/K4m/GIcDZ1YmFpUoy3Vibvi1NL5pawzDcHM0IiIi7qUzMBGRMsrpdGIJCoHLzaBbrVjKB+DIOn09wpIyrnBpvLrGi4iIKGkXESmjHA4HDrsd/+btLrmcf4skHMcOk/f/+uP85B3MY4evU4RSJqVvgNwcCIuEqrXcHY2IiIjbKWkXESnDztodBD/0OJag4As+bwkKJnjgo5xZlQr2PMyVS3D+4xEcY/+NuXfHdY5WygJzvUrjRUREfk9Ju4hIGWaz2cj18SNyzFT8W3f8rVTeasW/dUcix0wl168cOZ26YXnyFWh4I5gmbPoe56iROEaNxNz0PabT6d4XIqWCmavSeBERkT/ycncAIiLiXlnnbPj7+xM0/FlCH38eMzsLIyAIh91Ott2B7Zwtf8azdjzW2vGYRw9hLpmH+f0y2LsD594dEF0Jo0sPjBZJGN4+7n5JUlKlr4fzuRAeBTfUdHc0IiIiHkEz7SIigs1mI+NMNqfOZOMVEc2pM9lknMnGZrMVWdaIqYIl5VEsr76PcfOd4F8ejh3B/OQdnE8/hPOL2Zhns93wKqSkM9d9C4DRRKXxIiIiBZS0i4iIi+PX2785LncbOMAICcNy5/1YRn2IcfdACA2HzF8w507GOfIBnDM/xDx18lqHLKWEmZuDuXUdAEYzlcaLiIgUUHm8iIj8JYZ/OYwu3TE73Ia57lvMxXPgyA+YX8/HXPoZRrM2GMk9MSpXc3eo4sHMLevh/HmIiIYqNdwdjoiIiMdQ0i4iIleF4eWN0bI9Zosk2JaGc/Fc2LkFc81yzDXLIa4xlpt7Qt0GKn2WIswNv5bGq2u8iIhIIUraRUTkqjIMAxKaYE1ogvnDXszFc/Nv47V9I87tG6FK9fyZ9yatMQq61UuZZubYYOt6QF3jRURE/kjXtIuIyDVj3FATy8NPYnl5PEb728DHBw7tx3z/dZzPDsL5zWeYuTnuDlPczNz6a2l8ZEWoXN3d4YiIiHgUJe0iInLNGRHRWO4dhOXVjzDuuBcCguDUCcwZ7+N8aiDOeVMws067O0xxE3N9QWn8TSqNFxER+QOVx4uIyHVjBAZhdO2N2aUH5nffYC6ZByePYS6chbl4LkarjhhdumNExbg7VLlOzJxzsHUDoNJ4ERGRC1HSLiIi153h64uRdCtm22TYuAbn4jlwYDfmikWYKxdD4xZYuvTAqFHX3aHKNWZuXgd55yGqEsRWdXc4IiIiHkdJu4iIuI1hsUKTVlgSW8KebTgXzclvSJb2Hc6076BmXH7H+fpNMSy6oqs0MtevAshvTKjSeBERkSKUtIuIiNsZhgG1E7DWTsA8cgjzq7mY3y+HvdtxvrMdomMxkntgNE/C8PZ2d7hylZi2c5D+a2l8s9ZujkZERMQzadpCREQ8ilGpCpaUEVheeR8juSf4l4NjhzEnvY3z6Ydwfvk/zHPZ7g5TrgJz81qw50F0JahU1d3hiIiIeCQl7SIi4pGM0DAsd6VgGfURxl0DICQMMn/GnPMJzqcewDnrQ8yfT7o7TPkLzA2/lsara7yIiMhFqTxeREQ8muFfDiO5B2bH2zHXrsBcPBeOHsL8aj7m0s8xmrXFSO6OEVvN3aFKMRQqjVfXeBERkYtS0i4iIiWC4eWN0aojZssOkL4B5+K5sGsr5vepmN+nQkIili49oG4DzdqWAObmNWC3Q8XKEFPF3eGIiIh4LCXtIiJSohiGAfWbYq3fFPPAHszFczDTvoP0NJzpaXBDzfymdYmtMKxWd4crF+HqGt9UXeNFREQuRUm7iIiUWEa1WhiDR2Ke+Anz6/mYq76GH/ZiTvgPZngURuduGK07Yfj6uTtU+R3zXDZsSwPAaKLSeBERkUtRIzoRESnxjMiKWO4djOXVjzC69oGAIMg4jjl9As6RD+CcPxUz67S7w5RfmZvWukrjjUoqjRcREbkUzbSLiEipYQQGYdzRBzO5J+bqbzC/mgcnj2F+PhNz8VyMVh0wunTHiIxxd6hlmrn+W0AN6ERERK6EknYRESl1DF9fjPa3YrZLhrTv8pvWHdyDuXwR5orF0LglluQeGNXruDvUMsc8mw3bNwH517OLiIjIpSlpFxGRUsuwWKHpTViatIbd6fnJ+9b1kLYaZ9pqqB2PpUtPqN8Ew6Irxq4Hc9MacNih0g0Y6hovIiJyWUraRUSk1DMMA+rUx1qnPuaRQ5hL5mKuWQ67t+HcvS3/2urkHhg3tsPw9nZ3uKWaueG3rvEiIiJyeZpWEBGRMsWoVAXLgBFYXnkfI7kH+PnDTz9ifvwWzqcfwrnoU8xzZ90dZqmUXxq/EVDXeBERkSvl8TPtNpuNmTNnsnbtWjIzM6lWrRopKSnUrFkTgLFjx7J8+fJC69SqVYuXX37ZHeGKiEgJYYSGYdw1APPWXpgrF2N+vQBO/4z56STMhbMw2t6M0bErRoVwd4daapibvgeHA2KrYlSMdXc4IiIiJYLHJ+3jx4/nxx9/ZNiwYVSoUIEVK1bw0ksvMXr0aCpUqABAo0aNGDp0qGsdLy+Pf1kiIuIhjHLlMZJ7YnbsirlmBeaSuXD01xL6bxZg3NgWo0sPjNiq7g61xFPXeBERkeLz6Oz2/PnzrFmzhqeeeoq4uDgAevXqxbp161iyZAm9e/cG8pP0kJCQK95uXl4eeXl5rt8Nw8Df39/1s6cqiM2TYxTPojEjxVWWx4zh7QM3dcJs1QEzfQPORXNgdzrmd6mY36ViJDTBuLknRp36ZfL9uZgrHTNmdhbs2AyApelNeg/LsLJ8nJE/R2NGiqu0jRmPTtodDgdOpxPvPzQF8vHxYefOna7ft2/fzoMPPkj58uWpV68effr0ITg4+KLbnTt3Lv/73/9cv1erVo1Ro0YRERFx9V/ENRAdHe3uEKSE0ZiR4irzY6ZSJUi+g9xd6Zz5dDK271Ix0zdgpm/Au1YcQXf2w79VewyrR3+MXleXGzPZi9fwi8OBd7XaRDduep2iEk9W5o8zUmwaM1JcpWXMGKZpmu4O4lL+/ve/4+XlxaOPPkpISAjffvstY8eOJTo6mjFjxrB69Wr8/PwIDw/nxIkTzJw5E6fTyauvvlok2S9wsZn2kydPYrfbr9dLKzbDMIiOjubYsWN4+J9NPITGjBSXxsyFmceP4vxqHuaqbyDvfP6DEdFYOnfHaN0Rw9fPvQG60ZWOGcfof2Bu24ilRz8st/W6jhGKp9FxRopLY0aKq6SMGS8vryuaOPb4KYJhw4Yxbtw4Bg8ejMVioVq1arRu3ZoDBw4A0KpVK9eyVapUoUaNGgwdOpS0tDSaN29+wW16e3tfNKH35D9qAdM0S0Sc4jk0ZqS4NGb+ILIilvuGYN5xL2bqQszUhXDyGM5p42HBVIz2t+X/C7x4lVdpd6kxY57Jwvy1NJ4mrTW2BNBxRopPY0aKq7SMGY9P2qOjo3nxxRfJycnBZrMRGhrK6NGjiYyMvODyoaGhRERE8NNPP13nSEVEpLQzAoMx7rgXM/lOzNVfYy6ZBxnHMT+bgbloDkbrThidu2FEVnR3qB7F3PgdOJ1QpTpGVIy7wxERESlRPD5pL+Dn54efnx/Z2dls3ryZvn37XnC5M2fOcOrUKUJDQ69zhCIiUlYYvr4Y7W/DbHszZtp3mIvnwA97MZd9gbl8ESS2wJJ8J0a1Wu4O1SOYG1YB6hovIiLyZ3h80r5p0yYAYmJiOHbsGJMnTyYmJoakpCRycnKYNWsWLVq0ICQkhJMnTzJ9+nQCAwO58cYb3Ru4iIiUeobVitHsJsymrWHXVpyL50L6BtiwGueG1VA7AcvNPSGhSanpYFtc5plM2LkFAKNJazdHIyIiUvJ4fNJ+7tw5pk+fzqlTpwgICKB58+b06dMHLy8vnE4nP/74IytWrODs2bOEhoYSHx/PY4895rqFm4iIyLVmGAbUbYC1bgPMwwfz7/G+dgXsTse5Ox1iquTf6715WwyvC/dUKa1cpfE31NRlAyIiIn+CxyftrVq1KtRs7vd8fHx49tlnr3NEIiIiF2fEVsUY+Dhm976Y33yGuWIxHD2E+fEYzHlTMDp1xWiTjFGuvLtDvS7M9QWl8ZplFxER+TMs7g5ARESkNDIqRGC5eyCWUR9i3Hk/BFeA06cw//cxzr89gPN/EzF/OeXuMK8pM+s07NwKqDReRETkz/L4mXYREZGSzCgXgHHznZgd78Bcuxxz8Vz46UfMxXMxv/4Mo3m7/NL5SlXcHepVZ6Z9B+avpfER0e4OR0REpERS0i4iInIdGN7eGK07YbbsAFs34FwyB3Zvw1z9Debqb6B+UyzJPaF2fKlpWmeu/xYAo5m6xouIiPxZStpFRESuI8NigYbNsDZshrl/V37H+Y3fwdb1OLeuh6q18jvON26BYbG6O9w/zcz6BXZvA1QaLyIi8lcoaRcREXETo3odrEP+hnn8KOZX8zBXL4WDe3COHwUR0RhdumO06ojh4+vuUIvNVRpfrTZGeJS7wxERESmx1IhORETEzYyoGCx9h2J59QOM2++B8oFw8hjm1PE4Rz6Ac8F0zDNZ7g6zWNQ1XkRE5OpQ0i4iIuIhjKAQLN3uy+843/thCIuE7CzMz6bj/NtAnNPGY5485u4wL8vM/AV2pwMqjRcREfmrVB4vIiLiYQxfP4yOt2Mm3YKZthpz0Rw4tA8z9QvMZYswmrTCSO6BUbWWu0O9IDNtNZgmVK+DERbp7nBERERKNCXtIiIiHsqwWjGatcFsehPs3IJzyVxIT8Nc/21+Z/Y69fM7zickelTHeVfX+KbqGi8iIvJXKWkXERHxcIZhQL2GWOs1xDx8AHPxPMx1K2DXVpy7tkKlG/Lv9X5jGwwvb7fGap4+BXu258fdpJVbYxERESkNdE27iIhICWLEVsPywONY/j0Bo3M38PWHIz9gTvwvzqcfxrlkLqbtnNviMzd8l18aX6MuRoUIt8UhIiJSWihpFxERKYGMChFYej2A5bUPMXr2h+BQOH0Kc/ZEnCMH4vzfx/mz3tfZb6XxakAnIiJyNag8XkREpAQzygVg3HIXZqdumGuWYS6eC8cOYy6eg/n1AowW7fJL52OqXPNYzF9Owd5fS+MTlbSLiIhcDUraRURESgHD2xvjps6YrTrC1vU4F82BvdsxV32DueobaNAMS3IPqBV/zZrWmWmr83+oWQ+jQvg12YeIiEhZo6RdRESkFDEsFmh4I9aGN2Lu25nfcX7j97BlHc4t66Ba7fyO842bY1isV3Xf6hovIiJy9SlpFxERKaWMGnWxDnka89gRzK/mY67+Bg7sxjn+VYisiNG5O0arDhg+vn95X+bPGbB3BxgGRqK6xouIiFwtakQnIiJSyhnRlbD0G4pl1AcYt/WCcgFw4ifMqeNw/u1BnJ/PwMzO+kv7MDesyv+hZj2M0LCrELWIiIiAknYREZEywwgKxdK9L5ZRH2L0fgjCIuFMJub8aThHPoBz2nuYJ4/9qW07VRovIiJyTag8XkREpIwx/PwxOnbFTLoVc8MqzMVz4NB+zNSFmMu+xGjaGiO5B8YNNa9oe/YTx2DfTpXGi4iIXANK2kVERMoow2rFuLEtZrM2sHNLfsf57Rsx163EXLcS6jbIb1oX3/iiHeetViu52zfgFVMZe0AQRkiF6/wqRERESjcl7SIiImWcYRhQryHWeg0xfzyQf4/3dSvzE/mdWyC2av693pu1wfDKP3Xw9/envJcVq5cXzhp1iXxjIg7bOc76+GOz2dz8ikREREoPJe0iIiLiYlSuhvHgE5g9+mN+vQBz5WI4fBDzo9GY8yZjdLyDkK698M3LIfPd0djWLAeHA6xW/Ju3I/ihx/Eu50/WOSXuIiIiV4Ma0YmIiEgRRlgElnsewDLqI4we/SAoBH7OwP/UcXxtZzkxoi+21UvzE3YAhwPb6qWcGNEX3/O5+Pv7uzV+ERGR0kJJu4iIiFyUUT4Ay613Y3n1A4z+wwi8sx+Zk8bizMq84PLOrEwyPxhNeS/rdY5URESkdFLSLiIiIpdlePvgnXQL1qiY/JL4S7B9vwyrlxdWqxJ3ERGRv0pJu4iIiFwRi8WCM+v0byXxF+Nw4MzKxGLRaYaIiMhfpU9TERERuSJOpxNLUAhcbgbdasUSFIzT6bwucYmIiJRmStpFRETkijgcDhx2O/7N211yOf8WSTjsdhyXm5EXERGRy1LSLiIiIlfsrN1B8EOPYwkKvuDzlqBggh98nLN2JewiIiJXg5J2ERERuWI2m41cHz8ix0zFv3XH30rlrVb8W3ckcsxUcn18sdl0n3YREZGrwcvdAYiIiEjJknXOhr+/P0HDnyX08ecxs7MwAoJw2O1k2x3YzilhFxERuVqUtIuIiEix2Ww2bICXlxeRkdGcOHECu93u7rBERERKHZXHi4iIyJ9W0GxOTedERESuDSXtIiIiIiIiIh5KSbuIiIiIiIiIh1LSLiIiIiIiIuKhlLSLiIiIiIiIeCgl7SIiIiIiIiIeSkm7iIiIiIiIiIdS0i4iIiIiIiLioZS0i4iIiIiIiHgoJe0iIiIiIiIiHkpJu4iIiIiIiIiHUtIuIiIiIiIi4qGUtIuIiIiIiIh4KC93B+BJvLxKxttRUuIUz6ExI8WlMSPFpTEjxaUxI8WlMSPF5elj5krjM0zTNK9xLCIiIiIiIiLyJ6g8vgSx2WyMHDkSm83m7lCkhNCYkeLSmJHi0piR4tKYkeLSmJHiKm1jRkl7CWKaJgcOHEDFEXKlNGakuDRmpLg0ZqS4NGakuDRmpLhK25hR0i4iIiIiIiLioZS0i4iIiIiIiHgoJe0liLe3N3fddRfe3t7uDkVKCI0ZKS6NGSkujRkpLo0ZKS6NGSmu0jZm1D1eRERERERExENppl1ERERERETEQylpFxEREREREfFQStpFREREREREPJSS9lJk1qxZPPnkk+4OQ0qgRx55hIULF7o7DLnKli1bRkpKiltjOHHiBL169eLgwYNujUM872/xwgsv8PHHH7s7DLlGevXqxdq1ay/6vKeNRyldxo4dy2uvvebuMMRDlcScycvdAZQWY8eOZfny5XTq1ImHH3640HMffPABS5YsoV27djzyyCNuilA8Ra9evS75vMZJ6bdkyRKmTJnCxIkTsVqtAOTk5DBgwABq1arFP//5T9eyO3bs4Pnnn+e///0vMTEx7gpZPNyVHFfuvvvu6xSNlEYF5zl/9NZbbxEdHV3k8QkTJlC+fPnrEZpcZ5mZmcycOZONGzeSmZlJ+fLlqVq1KnfffTe1a9e+7PrLli3j448/1pd28pfHUlmipP0qCgsLY/Xq1aSkpODj4wPA+fPnWbVqFeHh4W6OTjzFhAkTXD+vXr2amTNnMmbMGNdjBWNHSq+EhARycnLYt2+f60Npx44dhISEsG/fPnJzc/H19QVg27ZthIaGKmGXS7qS40p2dvY12bfdbsfLS6cTZUGjRo0YOnRooceCgoIK/V4wHkJCQq5jZHI9vfHGGzgcDh555BGioqLIzMxk69at1+wYcyk6/pRsnjSWPJ1G+VVUrVo1Tpw4wZo1a2jTpg0Aa9euJSwsjMjISNdyeXl5TJ48mdWrV2Oz2ahevTr3338/NWvWBPJP0l988UWee+45pk6dyuHDh6latSpDhw4tdOI+b948Fi5cSG5uLi1btizywbl3716mT5/OwYMHsdvtVK1alfvvv5/q1asD8O6775KVlcXf/vY31zoOh4PBgwfTp08fOnTocM3eq7Ls9ycy5cqVwzAM12MX+vZ57dq1vP7668yaNcv12Pr165k9ezaHDx8mNDSUdu3a0bNnT9es7axZs0hNTSUzM5PAwECaN2/OwIEDgfxvNceNG8fWrVsJCQmhd+/eRWL8/PPPSU1N5cSJEwQEBNCkSRP69u2Ln58fOTk5DBo0iCFDhtCiRYtCMY0ZM4YJEybg7+9/Fd+x0icmJobQ0FC2b9/uStq3bdtG06ZN2bZtG7t27aJBgwYAbN++nfj4eOx2OzNmzGDlypWcO3eOypUrc9999xEfH+/a7rJly5g5cyZnzpyhYcOG1K1bt9B+Z82axbp16+jatSszZ84kOzubxo0bM2jQINffzDRNFixYwFdffcUvv/xCTEwMd955p+tvnZ2dzUcffcTmzZvJyckhLCyMHj160L59eyD/uDNhwgSOHDlC5cqV6dmzZ6EYnE4n7733Hunp6Zw+fZrw8HCSk5O59dZbXa/3pZdeYty4cYX+X/nkk0/Yt28fL7744lX8S5QelzquFCg4CTp+/DiTJk1iz549VKxYkYceesg1DgvGyH/+8x/XegsXLuSLL75g7NixQP6M69mzZ6lVqxaLFi3Cy8uLsWPHsnjxYhYuXMipU6coV64cdevW5YknngDyK0k++OAD1qxZg7+/P127di3yGlasWMEXX3zB0aNH8fX1JSEhgZSUFIKDgzFNk0cffZTOnTtzxx13uNY5dOgQTz75JGPGjLngbK9cXRdKxl944QUqV66Ml5cXK1asIDY2lhdffJFevXrxf//3f9x4442Ajg2lxdmzZ9m5cycvvPACcXFxAERERLjOYeHS5xDbtm3j3XffBX6rELrrrrvo1atXkTEDkJKSQkpKCklJSZw4cYJhw4bx2GOPsWTJEvbs2cODDz5Iu3btmDx5MqmpqVgsFjp06MAf72i9adMmPv30U3788UcsFgu1a9cmJSXFddx48cUXiY2N5YEHHnCtc+bMGQYNGsQzzzxDQkLCtXlDy7DLjaWCv/drr71G1apVXesMGDCA559/nvj4+DKVMylpv8qSkpJYtmyZK2lPTU2lffv2bNu2zbXMlClTWLNmDY888ggRERHMnz+fl19+mbfffpuAgADXcjNmzKB///4EBQXx/vvvM27cOF566SUgfyZl1qxZPPDAA9SrV48VK1bw5ZdfFvpyICcnh3bt2jFgwAAg/yD6yiuv8NZbb+Hv70/Hjh15/vnn+eWXXwgNDQVg48aN5OTk0KpVq2v+Xsmfs2nTJt5++20GDBhAvXr1OH78OO+99x4Ad999N99//z0LFy7kscceo3Llypw+fbrQNYPvvvsuGRkZPP/883h5eTFx4kQyMzML7cMwDAYMGEBkZCQnTpzggw8+YMqUKTz44IP4+fnRqlUrUlNTCyXty5Yto3nz5krYr1DBh0337t2B/KS9W7dumKbJtm3baNCgAXa7nd27dzNw4EDeffddTp48yWOPPUZoaChr167l3//+N6+//joVK1Zkz549jBs3jj59+nDjjTeyadMmZs+eXWS/x48fZ+3atYwcOZKzZ88yevRo5s2bR58+fYD8487atWt58MEHqVixIjt27ODtt98mKCiIuLg4Zs6cyeHDh3nmmWcIDAzk2LFjnD9/Hsg/5rz66qskJCQwfPhwTpw4UaT80el0EhYWxuOPP05QUBC7du1iwoQJhISE0KpVK+Li4oiMjGTFihWu5MzhcLBy5Uruvffea/cHKUNmzJhBv379iI6OZsaMGYwZM4a33nrL9aXflUhPT6dcuXL8/e9/xzRN9u3bx8SJExk2bBh16tQhOzubHTt2uJafMmUK27Zt48knnyQkJIRp06axf/9+14kY5M+Y3XPPPcTExJCZmcmkSZN49913efrppzEMg/bt27Ns2bJCSXtqaip169ZVwu5my5cvp0uXLrz00ktFkiXQsaE08fPzw8/Pj7Vr11KrVi28vb2LLHOpc4g6deqQkpJSqBrIz8+vWDFMnTqV/v37M3ToULy8vPjss89ITU1l8ODBxMbG8vnnn7Nu3bpCX2rn5ORw++23U6VKFXJzc5k5cyavv/46r732GhaLhY4dO/Lhhx/Sv39/12tauXIloaGhhbYjV8+VjKUrVRZyJjWiu8ratm3Lzp07OXHiBCdPnmTnzp2uBB7yB8WSJUvo168fjRs3JjY2lkGDBuHj48PSpUsLbat3797ExcURGxtLt27d2LVrl+vk+IsvvqB9+/Z07NiRmJgYevfuTWxsbKH1ExISaNu2LbGxscTGxvLwww9z/vx5tm/fDkCdOnWIiYlhxYoVrnVSU1Np2bJlsQ+gcv3MnTuX7t27k5SURFRUFA0aNOCee+7h66+/BiAjI4OQkBDq169PeHg4NWvWpFOnTgAcPXqUjRs3MnjwYGrXrk316tUZPHiwa1wVuO2220hISCAyMpKEhATuuecevvvuO9fzHTt2ZPPmzfz8888AZGVlsWHDBlVnFENcXBw7d+7E4XBgs9k4ePAg9erVIy4uzvX/6O7duzl//jxxcXGsWrWKxx9/nHr16hEdHc0dd9xB3bp1SU1NBfKPCQ0bNqR79+7ExMRw66230rBhwyL7NU2TRx55hCpVqlCvXj3atm1Leno6kH98+vzzzxkyZAiNGjUiKiqKpKQk2rRpw1dffQXkj6+qVatSo0YNIiMjadCgAU2bNgXg22+/xel0MmTIECpXrkyTJk2KzKh6eXnRq1cvatasSWRkJG3atKFdu3aFxleHDh1crwsgLS3N9e24/HVdu3YlMTGRmJgYevXqxcmTJzl27FixtuHr68vgwYOpXLkyVapUISMjA19fX5o0aUJERATVqlVzzZDm5OSwdOlS+vXrR4MGDahSpQrDhg3D6XQW2maHDh1o3LgxUVFR1K5dmwEDBrhOigDat2/P0aNH2bt3L5Cf5K9cudJV5SHXXlpaGv369XP9e/PNNwGIjo6mb9++xMTEUKlSpSLr6dhQelitVoYOHcry5ctJSUnhueeeY9q0afzwww+uZS51DuHl5VWoGigkJKTY55y33XYbzZs3JzIykgoVKvDFF1/QvXt3WrRoQWxsLA899BDlypUrtE6LFi1o3rw5FStWpGrVqgwZMoRDhw5x+PBhAJo3b45hGKxbt861zrJly0hKSsIwjD/7dsklXMlYulJlIWfSTPtVFhQUROPGjVm+fDmmaZKYmFioBOP48eM4HA7q1KnjeszLy4uaNWu6DhwFbrjhBtfPBd/qZGVlER4ezpEjR+jcuXOh5WvVqlVoRr+gucO2bds4ffo0TqeT8+fPk5GR4VqmQ4cOfPPNN3Tr1o3MzEzS0tL4xz/+cXXeDLkm9u/fz969e5kzZ47rMafTSV5eHrm5ubRo0YKFCxcyfPhwGjZsSGJiIk2aNMFqtXLkyBGsVis1atRwrVupUqUizYLS09OZO3cuhw8fxmaz4XA4yMvLIycnBz8/P2rWrEnlypVZsWIF3bt3Z8WKFYSHh1OvXr3r9j6UdAkJCeTm5rJv3z6ys7OpWLEiwcHBxMXF8fbbb5OTk8P27dsJDw/nwIEDmKbJiBEjCm3Dbre7qnOOHDlSqKQQoHbt2mzatKnQYxEREYWqIUJCQlyVFocPHyYvL8/17fTv91OtWjUAunTpwhtvvMGBAwdo2LAhzZo1cx3PDh8+zA033OC6Hr8ghj9asmQJS5cu5eTJk5w/f95VilYgKSmJGTNmsHv3bmrXrq0vE6+yKlWquH4uKDPOzMy8YLJ1qW38/jrSBg0aEBERwbBhw2jUqBGNGjXixhtvxNfXl2PHjmG32wuNhYCAgCJ9Gg4cOMDs2bM5ePAg2dnZrhnbjIwMYmNjCQ0NJTExkaVLl1KzZk3S0tLIy8tTwnYdxcfH89BDD7l+9/X1ZcyYMa4S0ovRsaF0adGiBYmJiezcuZPdu3ezadMmFixYwODBg0lKSrrsOcRf9fvxdu7cOX755ZdC48lqtVK9evVCVR/Hjh1j5syZ7NmzhzNnzri+NMzIyKBKlSp4e3vTpk0bUlNTadWqFQcPHuSHH34ocR3GS5pLjaWCkvkrURZyJiXt10CHDh348MMPAQpdGwO4DiB//NbONM0ij/2+VLHguT/OTFxKwfUX999/PxEREXh7e/Pss89it9tdy7Rr145p06axe/dudu/eTWRkpBIvNzIMo0hpocPhKPS70+mkV69eNG/evMj63t7ehIeHM2bMGLZs2cKWLVv44IMPWLBgAS+88MIFyxb/6OTJk7zyyit07tyZe+65h4CAAHbu3Mn48eMLxdKhQwcWLVpE9+7dWbZsGe3bt9e30cUQHR1NWFgY6enpnD171vXhFBISQmRkJLt27WLbtm0kJCRgmiYWi4VRo0ZhsRQukCo4AbqSvy1QpAT692Ou4L9PP/00FSpUKLRcQYLWuHFj3n33XdLS0tiyZQv//Oc/SU5Opn///le0/9WrVzNp0iT69+9P7dq18ff3Z8GCBezZs8e1THBwME2aNGHZsmVERUWxceNGnn/++Svavlze75Ptgv9nC/72fxxfUPQYBBRKvgD8/f0ZNWoU27ZtY8uWLcyaNYvZs2fzyiuvXFFMOTk5/Otf/6Jhw4YMHz6coKAgMjIyePnllwt9ZnXo0IF33nmHlJQUV8L2x1jk2vH19b3gpQhXIxHTsaFk8fHxoUGDBjRo0IC77rqL8ePHM2vWLOLj46/oHOJCLnQOcaF1/sx4GzVqFOHh4QwaNIjQ0FBM0+SJJ54odHzp2LEjTz75JKdOnWLp0qUkJCQQERFR7H1J8VxsLBXcSef35zcXG0NlIWdSefw10KhRI+x2O3a7nUaNGhV6Ljo6Gi8vL3bu3Ol6zG63s3///mLNclSqVKnQBxlQ5PcdO3Zwyy23kJiY6GoSc+bMmULLBAYG0qxZM1JTU0lNTSUpKemKY5CrLygoiJycHFc5KFDkHrbVq1fn6NGjREdHF/lXcMLt4+ND06ZNGThwIC+88AK7d+/m0KFDxMbG4nA42L9/v2t7R48e5ezZs67f9+3bh9PpdJ04xcTE8MsvvxSJtU2bNmRkZPDFF1/w448/0q5du6v8bpR+8fHxbN++ne3btxf6RjkuLo7Nmzeze/du4uPjqVq1Kk6nk8zMzCJ/84KZ0tjY2CLHgN27dxcrntjYWLy9vcnIyCiyn9/fASMoKIikpCQeffRRUlJS+Oabb1zr//DDD4Uut/hjTDt37qROnTokJydTrVo1oqOjOX78eJFYOnbsyKpVq/jqq6+Iiooq0lRPro2goCBOnz5d6CTpSu+jbbVaadCgAX379uU///kPJ0+eJD09nejoaKxWa6HxmJ2dzU8//eT6/ejRo5w5c4Z7772XevXqUalSpSK9NgASExPx9fVlyZIlbNq0SZfklBA6NpR+sbGxruqxy51DeHl5XTChCgoKKrTsTz/9RG5u7iX3W65cOUJDQwuNpz+e55w5c4YjR47Qs2dP6tevT2xsbKHzngJVqlShRo0afPPNN6xatUqX3rhJwVgqqFT+/Zi40s+j3ystOZNm2q8Bi8XC6NGjXT//np+fH126dGHy5MkEBAQQHh7O/Pnzyc3NLdbJx6233srYsWOpXr06devW5dtvv+Xw4cOFmipER0ezYsUKqlevjs1mY8qUKRe8nVjHjh159dVXcTqdSrzcrFatWvj4+DB9+nRuueUW9u7dy7Jlywotc+eddzJq1CjCwsJo2bIlhmFw6NAhDh06RO/evVm2bBlOp5OaNWvi6+vLihUr8PHxISIigsDAQBo1asR7773Hww8/jNVq5eOPPy40LqKjo3E4HCxatIgmTZqwa9cu1/XMvxcQEEDz5s2ZMmUKDRs2JCws7Fq/PaVOfHw8H374IQ6Ho0jS/sEHH5CXl0d8fDzh4eHcdNNNvPPOO/Tv359q1aqRlZVFeno6VapUITExkVtuuYXnnnuO+fPn06xZM7Zs2cLmzZuLFU9BV+9JkybhdDqpW7cuNpuNXbt24efnR1JSEjNnzqR69epUrlyZvLw8NmzY4PrC8aabbmL69OmMGzeOO++8kxMnTvDZZ58V2kd0dDTLly9n06ZNrqZSe/fuLXTsAmjYsCHlypVjzpw5l70HuVw9cXFxZGVlMX/+fFq0aMGmTZvYuHFjketD/2jDhg0cP36cuLg4ypcvz8aNG3E6ncTExODn50eHDh2YMmUKgYGBBAcHM2PGjEKzauHh4Xh5ebFo0SI6d+7Mjz/+yKefflpkPxaLhaSkJKZNm0Z0dLTu41tC6NhQepw5c4Y333yT9u3bc8MNN+Dv78++ffuYP38+TZs2vaJziIiICHJycti6davrsglfX1/i4+NZtGgRtWrVwjRNpk6dekUNMm+55RbmzZtHxYoVqVSpEp9//jnnzp1zPV++fHkCAwP5+uuvCQ0NJSMjg6lTp15wWx06dOCjjz7C19e3yCVncnVdbiz5+PhQq1Yt5s+fT2RkJFlZWcyYMaPY+yktOZOS9mvkUic49957L06n03XdavXq1Xn22WcLdY6/nFatWnHs2DGmTp1KXl4ezZs3p3PnzoVO0ocMGcKECRMYOXIk4eHh9OnTh8mTJxfZVv369QkNDSU2NrZISaxcXwEBAQwfPpwpU6bw9ddfU79+fe6+++5C92Bu1KgRI0eO5NNPP2XBggVYrVYqVark+tKnXLlyzJ8/35V4ValShZEjRxIYGAjA0KFDGT9+PC+88ALBwcH07t2bmTNnurZftWpV+vfvz/z585k2bRr16tXj3nvv5Z133ikSb4cOHfj222/1bfSfFB8fz/nz56lUqVKhWxjFxcVhs9mIiopyzXAPHTqUOXPm8Mknn/Dzzz8TGBhI7dq1SUxMBPKvDx00aBCzZ89m9uzZ1K9fn549e14w8bmUe+65h6CgIObNm8fx48cpX7481apVo0ePHkD+DMm0adM4efIkPj4+1K1bl8ceewzI/1Jy5MiRvP/++zz11FPExsZy33338cYbb7i237lzZw4ePMh///tfDMOgdevWJCcns3HjxkJxFCRnc+fO1ZeJ11HBLY/mzp3Lp59+SvPmzenataurmuJiypcvz9q1a5k9ezZ5eXlUrFiRESNGULlyZQD69etHTk4Or732Gn5+fnTt2rXQSXVQUBBDhw5l+vTpfPnll1SrVo1+/frx2muvFdlXhw4dmDt3ro47JYiODaWHn58ftWrVYuHCha4+TWFhYXTs2JGePXvi4+Nz2XOIOnXq0LlzZ/773/9y5swZ1y3f+vfvz7hx43j++eepUKECKSkphWbML6Zr166cPn2asWPHYrFYaN++Pc2aNXMdYywWCyNGjGDixIk88cQTxMTEMGDAAF544YUi27rpppuYNGkSrVu3vmDSJlfP5cYS5Ocy48aN429/+xsxMTH07duXf/3rX8XaT2nJmQzzSi+ElFIrNzfXdd/tC10nLXIxK1eu5OOPP+a9994rdJ2syNUwfvx4MjMzGTlypLtDEQ+yc+dOXnzxxSL365ayQ8cGuVYyMjJ45JFHeOWVVy7bYFHKHnfmTLqmvQxzOp38/PPPzJw5k3Llyrlu2yRyObm5ufz444/MmzePTp06KWGXq+rcuXNs2bKFb7/9lltuucXd4YiHyMvLc3WAbtmypRL2MkjHBrlW7Ha7q2y+4Ja4IgU8IWfSmXYZlpGRwbBhwwgLC2Po0KFXdN2QCMD8+fOZO3cu9erVc5VNi1wtr732Gnv37qVTp040aNDA3eGIh1i1ahXjxo2jatWqDB8+3N3hiBvo2CDXyq5du3jxxRepWLEiTzzxhLvDEQ/jCTmTyuNFREREREREPJTK40VEREREREQ8lJJ2EREREREREQ+lpF1ERERERETEQylpFxEREREREfFQStpFREREREREPJSSdhEREREREREPpaRdRESkhElJScEwDAzDwNvbm6ioKDp37sxHH32E0+m8bvt/9dVXCz0+b948DMO45vsXEREpS5S0i4iIlEA333wzP/30EwcPHuTLL7+kffv2jBgxgttvvx273X7N9+/n58eoUaP45Zdfrvm+REREyjIl7SIiIiWQr68v0dHRVKpUicTERJ555hnmz5/Pl19+yccff+xa7s0336R+/fqUL1+eypUrM3ToULKzswE4e/YsQUFB/O9//yu07c8++4zy5ctz5syZi+6/U6dOREdH88orr1x0mVOnTtGnTx9iY2MpV64c9evXZ/r06YWWSUpKYvjw4Tz22GOEhoYSFRXFhAkTOHv2LAMGDCAwMJAaNWrw5ZdfFlpv+/bt3HrrrQQEBBAVFUW/fv3IyMi40rdPRESkxFDSLiIiUkp06NCBhg0bMmfOHNdjFouFt956i/T0dCZNmsTSpUt56qmnAChfvjy9e/dm4sSJhbYzceJE7rrrLgIDAy+6L6vVyr///W/efvttDh8+fMFlcnJyaNKkCZ9//jnp6ek8/PDD9OvXjzVr1hRabtKkSYSHh7N27VqGDx/OkCFDuPvuu2nVqhVpaWkkJyfTr18/zp07B8BPP/1Eu3btaNSoEevXr2fRokUcP36cXr16/an3TURExJMZpmma7g5CRERErlxKSgqnT59m3rx5RZ7r3bs3W7ZsYfv27Rdcd/bs2QwZMsQ1K7127VpatWrFoUOHiImJISMjg5iYGL766ivatWt32f23bNmSuLg4PvzwQ+bNm0ePHj241KnFbbfdRr169Xj99deB/Jl2h8PBypUrAXA4HAQHB9OzZ08++eQTAI4dO0bFihX57rvvaNGiBf/4xz9Ys2YNixcvdm338OHDVK5cmV27dlG7du3Lv4kiIiIlhGbaRUREShHTNAs1g0tNTaVz585UqlSJwMBA+vfvz6lTpzh79iwAN954I/Hx8a4EefLkyVSpUoW2bdte0f5GjRrFpEmTLvglgcPh4OWXX6ZBgwaEhYUREBDAkiVLOHToUKHlGjRo4PrZarUSFhZG/fr1XY9FRUUBcOLECQA2bNhAamoqAQEBrn9169YFYN++fVcUt4iISEmhpF1ERKQU2bFjB9WqVQPghx9+4NZbbyUhIYFPP/2UDRs2MHbsWADy8vJc6zz44IOuEvmJEycyYMCAK+4C37ZtW5KTk3nmmWeKPPfGG28wevRonnrqKZYuXcqmTZtITk7m/PnzhZbz9vYu9HtBV/zf/w64OuM7nU66du3Kpk2bCv3bs2fPFX/ZICIiUlJ4uTsAERERuTqWLl3K1q1befzxxwFYv349drudN954A4sl/3v6WbNmFVmvb9++PPXUU7z11lts27aN+++/v1j7ffXVV2nUqFGRsvSVK1fSrVs3+vbtC+Qn23v27KFevXp/5uW5JCYm8umnn1K1alW8vHQqIyIipZtm2kVEREqg3Nxcjh07xpEjR0hLS+Pf//433bp14/bbb6d///4A1KhRA7vdzttvv83+/fuZPHky48ePL7Kt0NBQevbsyZNPPkmXLl2IjY0tViz169fnvvvu4+233y70eM2aNfnqq69YvXo1O3bsYNCgQRw7duzPv+hfPfLII/z888/06dOHtWvXsn//fpYsWcLAgQNxOBx/efsiIiKeREm7iIhICbRo0SIqVqxI1apVufnmm0lNTeWtt95i/vz5WK1WABo1asSbb77JqFGjSEhIYOrUqRe9RdsDDzzA+fPnGThw4J+K56WXXirSgO65554jMTGR5ORkkpKSiI6Opnv37n9q+78XExPDqlWrcDgcJCcnk5CQwIgRIwgODnZVFIiIiJQW6h4vIiIiTJ06lREjRnD06FF8fHzcHY6IiIj8SheCiYiIlGHnzp3jwIEDvPLKKwwaNEgJu4iIiIdRDZmIiEgZ9tprr9GoUSOioqJ4+umn3R2OiIiI/IHK40VEREREREQ8lGbaRURERERERDyUknYRERERERERD6WkXURERERERMRDKWkXERERERER8VBK2kVEREREREQ8lJJ2EREREREREQ+lpF1ERERERETEQylpFxEREREREfFQ/x9ZZO/M4FmWuAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Copying dataframe\n",
    "daily_trend = df.copy()\n",
    "\n",
    "# Creating column dayname\n",
    "daily_trend['DAYNAME'] = daily_trend['START_DATE'].apply(lambda x: x.strftime('%A'))\n",
    "\n",
    "# Counting orders per dayname\n",
    "daily_trend = daily_trend.groupby(['DAYNAME']).size()\n",
    "\n",
    "# Creating day name order\n",
    "day_order = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']\n",
    "\n",
    "# Creating figure and axes object\n",
    "fig, ax = plt.subplots(figsize=(12,6))\n",
    "\n",
    "# Plotting\n",
    "sns.lineplot(\n",
    "    x = daily_trend.loc[day_order].index,\n",
    "    y = daily_trend.loc[day_order].values,\n",
    "    ax = ax,\n",
    "    marker = '.',\n",
    "    markersize = 15\n",
    ")\n",
    "\n",
    "# Customizing\n",
    "ax.set_title('Uber Order Trend by Day\\n01 Jan 2016 - 31 Dec 2016')\n",
    "ax.set_xlabel('Day Name')\n",
    "ax.set_ylabel('Total Orders')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cce6c62",
   "metadata": {
    "papermill": {
     "duration": 0.037918,
     "end_time": "2023-09-05T11:55:38.570492",
     "exception": false,
     "start_time": "2023-09-05T11:55:38.532574",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Insights\n",
    "- Surprisingly, orders are less likely to occur on Wednesdays than on weekend days.\n",
    "- Orders are skyrocketing on Friday.\n",
    "- Low orders on the weekend can be associated with the customer segment proportion which implies ~93% of customers are ordering Uber for business purposes."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9657e398",
   "metadata": {
    "papermill": {
     "duration": 0.037458,
     "end_time": "2023-09-05T11:55:38.645977",
     "exception": false,
     "start_time": "2023-09-05T11:55:38.608519",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# How is the monthly trend for Uber trips?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "a0dfa40e",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:38.725158Z",
     "iopub.status.busy": "2023-09-05T11:55:38.724307Z",
     "iopub.status.idle": "2023-09-05T11:55:39.109723Z",
     "shell.execute_reply": "2023-09-05T11:55:39.108458Z"
    },
    "papermill": {
     "duration": 0.428131,
     "end_time": "2023-09-05T11:55:39.112580",
     "exception": false,
     "start_time": "2023-09-05T11:55:38.684449",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Copying dataframe\n",
    "monthly_trend = df.copy()\n",
    "\n",
    "# Creating column month\n",
    "monthly_trend['MONTH'] = monthly_trend['START_DATE'].apply(lambda x: x.strftime('%b'))\n",
    "\n",
    "# Counting orders per month\n",
    "monthly_trend = monthly_trend.groupby(['MONTH']).size()\n",
    "\n",
    "# Creating month name order\n",
    "month_order = [\n",
    "    'Jan', \n",
    "    'Feb', \n",
    "    'Mar', \n",
    "    'Apr', \n",
    "    'May',\n",
    "    'Jun',\n",
    "    'Jul',\n",
    "    'Aug',\n",
    "    'Sep',\n",
    "    'Oct',\n",
    "    'Nov',\n",
    "    'Dec'\n",
    "]\n",
    "\n",
    "# Creating figure and axes object\n",
    "fig, ax = plt.subplots(figsize=(12,6))\n",
    "\n",
    "# Plotting\n",
    "sns.lineplot(\n",
    "    x = monthly_trend.loc[month_order].index,\n",
    "    y = monthly_trend.loc[month_order].values,\n",
    "    ax = ax,\n",
    "    marker = '.',\n",
    "    markersize = 15\n",
    ")\n",
    "\n",
    "ax.set_title('Uber Order Trend by Month\\n01 Jan 2016 - 31 Dec 2016')\n",
    "ax.set_xlabel('Month Name')\n",
    "ax.set_ylabel('Total Orders')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d20dcb27",
   "metadata": {
    "papermill": {
     "duration": 0.039103,
     "end_time": "2023-09-05T11:55:39.192027",
     "exception": false,
     "start_time": "2023-09-05T11:55:39.152924",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Insights\n",
    "- The orders are increasing and considered in the relatively high amount in Q1.\n",
    "- The orders are declining at the beginning of Q2 but increase at the end of the quarter.\n",
    "- In Q3, it increased at the beginning of the quarter, however, it declined steeply at the end of the quarter.\n",
    "- And the order experienced a good increasing trend in the last quarter (Q4)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e088b01",
   "metadata": {
    "papermill": {
     "duration": 0.039665,
     "end_time": "2023-09-05T11:55:39.271169",
     "exception": false,
     "start_time": "2023-09-05T11:55:39.231504",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Is there any specific characteristic of each segment based on their travel distance?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "ed6e993f",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:39.354798Z",
     "iopub.status.busy": "2023-09-05T11:55:39.354142Z",
     "iopub.status.idle": "2023-09-05T11:55:39.817709Z",
     "shell.execute_reply": "2023-09-05T11:55:39.816406Z"
    },
    "papermill": {
     "duration": 0.507791,
     "end_time": "2023-09-05T11:55:39.820131",
     "exception": false,
     "start_time": "2023-09-05T11:55:39.312340",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Copying dataframe\n",
    "avg_distance = df.copy()\n",
    "\n",
    "# Creating figure and axes object\n",
    "plt.figure(figsize=(15, 6))\n",
    "\n",
    "# Plotting\n",
    "sns.boxplot(data=avg_distance, x='MILES', y='PURPOSE')\n",
    "plt.xlabel('Travel Distance')\n",
    "plt.ylabel('Purpose')\n",
    "plt.title('Distribution of Travel Distance by Customer Segment\\n01 Jan 2016 - 31 Dec 2016')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e29b21e8",
   "metadata": {
    "papermill": {
     "duration": 0.039619,
     "end_time": "2023-09-05T11:55:39.900168",
     "exception": false,
     "start_time": "2023-09-05T11:55:39.860549",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Insights\n",
    "- Again, we can see that our `MILES` data consists of many outliers.\n",
    "- Customers who have Errand/Supplies purpose tend to have relatively low travel distance.\n",
    "- On median, customers who have a Meeting purpose travel further than most of the other purposes.\n",
    "- Customers who have Customer Visit purposes have relatively higher variability than the other purposes."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31e1bb17",
   "metadata": {
    "papermill": {
     "duration": 0.040022,
     "end_time": "2023-09-05T11:55:39.981724",
     "exception": false,
     "start_time": "2023-09-05T11:55:39.941702",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Is there any specific characteristic of each segment based on the travel duration?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "d77c8bc6",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2023-09-05T11:55:40.064304Z",
     "iopub.status.busy": "2023-09-05T11:55:40.063562Z",
     "iopub.status.idle": "2023-09-05T11:55:40.527138Z",
     "shell.execute_reply": "2023-09-05T11:55:40.526175Z"
    },
    "papermill": {
     "duration": 0.507589,
     "end_time": "2023-09-05T11:55:40.529419",
     "exception": false,
     "start_time": "2023-09-05T11:55:40.021830",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Copying dataframe\n",
    "travel_time = df.copy()\n",
    "\n",
    "# Creating column duration\n",
    "travel_time['DURATION'] = (travel_time['END_DATE'] - travel_time['START_DATE']).dt.total_seconds()/60\n",
    "\n",
    "# Plotting\n",
    "fig, ax = plt.subplots(figsize = (12,6))\n",
    "sns.boxplot(\n",
    "    x = travel_time['DURATION'], \n",
    "    y = travel_time['PURPOSE'],\n",
    "    ax = ax\n",
    ")\n",
    "\n",
    "# Customizing\n",
    "ax.set_title('Travel Time by Customer Segment Distribution\\n01 Jan 2016 - 31 Dec 2016')\n",
    "ax.set_xlabel('Travel Time (in Minutes)')\n",
    "ax.set_ylabel('Purpose')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4157bed",
   "metadata": {
    "papermill": {
     "duration": 0.041298,
     "end_time": "2023-09-05T11:55:40.611746",
     "exception": false,
     "start_time": "2023-09-05T11:55:40.570448",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Insights\n",
    "- We can see that our trip duration data also consists of many outliers.\n",
    "- On the median, customers who have Errand/Supplies purpose tend to have relatively low travel duration.\n",
    "- Customers with Meal/Entertain purposes have relatively low travel duration compared to other purposes in the Business category.\n",
    "- On a median, customers who have Meetings, Customer Visits, Temporary Sites, and Between Offices purposes have similar travel duration.\n",
    "- Customers who have Customer Visit purposes have relatively higher variability than the other purposes."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "daf5ebac",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-07-28T07:05:00.929066Z",
     "iopub.status.busy": "2023-07-28T07:05:00.927722Z",
     "iopub.status.idle": "2023-07-28T07:05:00.933691Z",
     "shell.execute_reply": "2023-07-28T07:05:00.932602Z",
     "shell.execute_reply.started": "2023-07-28T07:05:00.929011Z"
    },
    "papermill": {
     "duration": 0.041181,
     "end_time": "2023-09-05T11:55:40.694479",
     "exception": false,
     "start_time": "2023-09-05T11:55:40.653298",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Closing statement.\n",
    "\n",
    "Thanks for taking the time to read this notebook. Your support and engagement mean a lot to me. Mistakes are part of the learning process, and I appreciate any feedback or insights you have to offer.\n",
    "\n",
    "As I continue on my data science journey, I'll carry your encouragement with me. Together, we'll explore new horizons and unlock the mysteries of our data-driven world.\n",
    "\n",
    "It's been a pleasure sharing this adventure with you. Looking forward to crossing paths again soon!"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 30.707793,
   "end_time": "2023-09-05T11:55:41.859070",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2023-09-05T11:55:11.151277",
   "version": "2.4.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}