{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"collapsed_sections":["7tvsecMeNCh2"],"authorship_tag":"ABX9TyP5XBeD4kL9ex6OOmuw7Ibg"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","source":["# This notebook is intended to uncover the popular Citi bike routes\n","\n","Popular routes are defined to be routes starting from a popular start station and end at a popular station. A popular station is defined to be a station having top rides either started at or ended at.<br>\n","We are interested in popular routes between popular stations.<br>\n","The definition of popular is more restrictive since we are saying a station to be a popular one with the criteria of looking at if it has top departure rides or arrival rides rather than the sum of two types of rides."],"metadata":{"id":"OgJvkbgP881P"}},{"cell_type":"markdown","source":["## Import essential libraries"],"metadata":{"id":"B9zEH7lcwIY-"}},{"cell_type":"code","source":["# import libraries\n","import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","import glob\n","import os"],"metadata":{"id":"DSlfFQP39CYF","executionInfo":{"status":"ok","timestamp":1725563322873,"user_tz":240,"elapsed":294,"user":{"displayName":"Wangsheng Wu","userId":"00552226409306193312"}}},"execution_count":58,"outputs":[]},{"cell_type":"code","source":["# Mount the drive\n","from google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"id":"1rHSCoUh45Mx","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1725563323953,"user_tz":240,"elapsed":1084,"user":{"displayName":"Wangsheng Wu","userId":"00552226409306193312"}},"outputId":"2a2a11aa-54ee-4fd7-cf37-58b526f5e764"},"execution_count":59,"outputs":[{"output_type":"stream","name":"stdout","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"]}]},{"cell_type":"code","source":["df = pd.read_csv('/content/drive/MyDrive/afterschool_projects/ny_bike/citi_sampled_data_2023_small.csv')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Ne0FPAX35G-A","executionInfo":{"status":"ok","timestamp":1725563328330,"user_tz":240,"elapsed":876,"user":{"displayName":"Wangsheng Wu","userId":"00552226409306193312"}},"outputId":"fb29dc38-4f34-4b89-bc1b-9d02abc142a8"},"execution_count":60,"outputs":[{"output_type":"stream","name":"stderr","text":["<ipython-input-60-393b0aff0b49>:1: DtypeWarning: Columns (5) have mixed types. Specify dtype option on import or set low_memory=False.\n","  df = pd.read_csv('/content/drive/MyDrive/afterschool_projects/ny_bike/citi_sampled_data_2023_small.csv')\n"]}]},{"cell_type":"code","source":["df.shape"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"acstjDJr_GVT","executionInfo":{"status":"ok","timestamp":1725563328330,"user_tz":240,"elapsed":4,"user":{"displayName":"Wangsheng Wu","userId":"00552226409306193312"}},"outputId":"8414fbcf-69f2-415d-f87a-116543cfe2b2"},"execution_count":61,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(35004, 20)"]},"metadata":{},"execution_count":61}]},{"cell_type":"code","source":["df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":309},"id":"MEAiKh9dNKzY","executionInfo":{"status":"ok","timestamp":1725563329068,"user_tz":240,"elapsed":740,"user":{"displayName":"Wangsheng Wu","userId":"00552226409306193312"}},"outputId":"43b6a683-159e-4513-d490-c462a456a32a"},"execution_count":62,"outputs":[{"output_type":"execute_result","data":{"text/plain":["            ride_id  rideable_type               started_at  \\\n","0  866D455C8D1C2A22  electric_bike  2023-10-08 17:14:27.462   \n","1  E3B6FF4A05756395   classic_bike  2023-08-06 08:51:43.861   \n","2  03B60B94F91D48B1  electric_bike  2023-10-22 22:29:25.387   \n","3  04AB87E8DFAC305F  electric_bike  2023-04-19 15:49:00.015   \n","4  3E02C4169CD1CA5E   classic_bike  2023-04-25 15:45:45.132   \n","\n","                  ended_at       start_station_name start_station_id  \\\n","0  2023-10-08 17:25:21.035     West St & Liberty St          5184.08   \n","1  2023-08-06 09:01:41.778     William St & Pine St          5065.12   \n","2  2023-10-22 22:47:47.328          E 53 St & 3 Ave          6617.02   \n","3  2023-04-19 15:56:09.629  Amsterdam Ave & W 66 St          7149.05   \n","4  2023-04-25 16:25:46.709   University Pl & E 8 St          5755.14   \n","\n","          end_station_name end_station_id  start_lat  start_lng    end_lat  \\\n","0  W 16 St & The High Line        6233.05  40.711701 -74.014969  40.743349   \n","1   N Moore St & Hudson St        5470.02  40.707179 -74.008873  40.719961   \n","2    LaGuardia Pl & W 3 St        5721.14  40.757457 -73.969121  40.729170   \n","3          3 Ave & E 62 St        6762.04  40.774397 -73.984702  40.763126   \n","4    Washington Pl & 6 Ave        5838.09  40.731437 -73.994903  40.732241   \n","\n","     end_lng member_casual   ride_date  ride_year  ride_month  ride_day  \\\n","0 -74.006818        member  2023-10-08       2023          10         8   \n","1 -74.008443        casual  2023-08-06       2023           8         6   \n","2 -73.998102        member  2023-10-22       2023          10        22   \n","3 -73.965269        member  2023-04-19       2023           4        19   \n","4 -74.000264        member  2023-04-25       2023           4        25   \n","\n","   is_weekend                duration  duration_minutes  \n","0        True  0 days 00:10:53.573000              10.9  \n","1        True  0 days 00:09:57.917000              10.0  \n","2        True  0 days 00:18:21.941000              18.4  \n","3       False  0 days 00:07:09.614000               7.2  \n","4       False  0 days 00:40:01.577000              40.0  "],"text/html":["\n","  <div id=\"df-68557311-513b-4cf3-afd0-51b6ad0c523d\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>ride_id</th>\n","      <th>rideable_type</th>\n","      <th>started_at</th>\n","      <th>ended_at</th>\n","      <th>start_station_name</th>\n","      <th>start_station_id</th>\n","      <th>end_station_name</th>\n","      <th>end_station_id</th>\n","      <th>start_lat</th>\n","      <th>start_lng</th>\n","      <th>end_lat</th>\n","      <th>end_lng</th>\n","      <th>member_casual</th>\n","      <th>ride_date</th>\n","      <th>ride_year</th>\n","      <th>ride_month</th>\n","      <th>ride_day</th>\n","      <th>is_weekend</th>\n","      <th>duration</th>\n","      <th>duration_minutes</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>866D455C8D1C2A22</td>\n","      <td>electric_bike</td>\n","      <td>2023-10-08 17:14:27.462</td>\n","      <td>2023-10-08 17:25:21.035</td>\n","      <td>West St &amp; Liberty St</td>\n","      <td>5184.08</td>\n","      <td>W 16 St &amp; The High Line</td>\n","      <td>6233.05</td>\n","      <td>40.711701</td>\n","      <td>-74.014969</td>\n","      <td>40.743349</td>\n","      <td>-74.006818</td>\n","      <td>member</td>\n","      <td>2023-10-08</td>\n","      <td>2023</td>\n","      <td>10</td>\n","      <td>8</td>\n","      <td>True</td>\n","      <td>0 days 00:10:53.573000</td>\n","      <td>10.9</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>E3B6FF4A05756395</td>\n","      <td>classic_bike</td>\n","      <td>2023-08-06 08:51:43.861</td>\n","      <td>2023-08-06 09:01:41.778</td>\n","      <td>William St &amp; Pine St</td>\n","      <td>5065.12</td>\n","      <td>N Moore St &amp; Hudson St</td>\n","      <td>5470.02</td>\n","      <td>40.707179</td>\n","      <td>-74.008873</td>\n","      <td>40.719961</td>\n","      <td>-74.008443</td>\n","      <td>casual</td>\n","      <td>2023-08-06</td>\n","      <td>2023</td>\n","      <td>8</td>\n","      <td>6</td>\n","      <td>True</td>\n","      <td>0 days 00:09:57.917000</td>\n","      <td>10.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>03B60B94F91D48B1</td>\n","      <td>electric_bike</td>\n","      <td>2023-10-22 22:29:25.387</td>\n","      <td>2023-10-22 22:47:47.328</td>\n","      <td>E 53 St &amp; 3 Ave</td>\n","      <td>6617.02</td>\n","      <td>LaGuardia Pl &amp; W 3 St</td>\n","      <td>5721.14</td>\n","      <td>40.757457</td>\n","      <td>-73.969121</td>\n","      <td>40.729170</td>\n","      <td>-73.998102</td>\n","      <td>member</td>\n","      <td>2023-10-22</td>\n","      <td>2023</td>\n","      <td>10</td>\n","      <td>22</td>\n","      <td>True</td>\n","      <td>0 days 00:18:21.941000</td>\n","      <td>18.4</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>04AB87E8DFAC305F</td>\n","      <td>electric_bike</td>\n","      <td>2023-04-19 15:49:00.015</td>\n","      <td>2023-04-19 15:56:09.629</td>\n","      <td>Amsterdam Ave &amp; W 66 St</td>\n","      <td>7149.05</td>\n","      <td>3 Ave &amp; E 62 St</td>\n","      <td>6762.04</td>\n","      <td>40.774397</td>\n","      <td>-73.984702</td>\n","      <td>40.763126</td>\n","      <td>-73.965269</td>\n","      <td>member</td>\n","      <td>2023-04-19</td>\n","      <td>2023</td>\n","      <td>4</td>\n","      <td>19</td>\n","      <td>False</td>\n","      <td>0 days 00:07:09.614000</td>\n","      <td>7.2</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>3E02C4169CD1CA5E</td>\n","      <td>classic_bike</td>\n","      <td>2023-04-25 15:45:45.132</td>\n","      <td>2023-04-25 16:25:46.709</td>\n","      <td>University Pl &amp; E 8 St</td>\n","      <td>5755.14</td>\n","      <td>Washington Pl &amp; 6 Ave</td>\n","      <td>5838.09</td>\n","      <td>40.731437</td>\n","      <td>-73.994903</td>\n","      <td>40.732241</td>\n","      <td>-74.000264</td>\n","      <td>member</td>\n","      <td>2023-04-25</td>\n","      <td>2023</td>\n","      <td>4</td>\n","      <td>25</td>\n","      <td>False</td>\n","      <td>0 days 00:40:01.577000</td>\n","      <td>40.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-68557311-513b-4cf3-afd0-51b6ad0c523d')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-68557311-513b-4cf3-afd0-51b6ad0c523d button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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40.64535\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"end_lng\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.027907499894036483,\n        \"min\": -74.04595255851744,\n        \"max\": -73.853,\n        \"num_unique_values\": 1977,\n        \"samples\": [\n          -74.04595255851744,\n          -73.89246\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"member_casual\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"casual\",\n          \"member\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ride_date\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 365,\n        \"samples\": [\n          \"2023-10-09\",\n          \"2023-06-29\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ride_year\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 2023,\n        \"max\": 2023,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          2023\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ride_month\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3,\n        \"min\": 1,\n        \"max\": 12,\n        \"num_unique_values\": 12,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ride_day\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8,\n        \"min\": 1,\n        \"max\": 31,\n        \"num_unique_values\": 31,\n        \"samples\": [\n          12\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"is_weekend\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"duration\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 34538,\n        \"samples\": [\n          \"0 days 00:16:12.447000\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"duration_minutes\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 35.923719082875465,\n        \"min\": 1.0,\n        \"max\": 4214.5,\n        \"num_unique_values\": 931,\n        \"samples\": [\n          69.4\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":62}]},{"cell_type":"markdown","source":["## filter the dataset for top stations\n"],"metadata":{"id":"7tvsecMeNCh2"}},{"cell_type":"code","source":["dff = df.groupby(['start_station_name', 'end_station_name', 'ride_month']).agg(route_cnt=('ride_id', 'count')).reset_index()"],"metadata":{"id":"NZbkTg7NNG2i"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["start_station = dff.groupby('start_station_name').agg(station_cnt=('route_cnt', 'sum')).reset_index()"],"metadata":{"id":"AIy9RH3sQEFV"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["start_station = start_station.sort_values(by='station_cnt', ascending=False).head(10)"],"metadata":{"id":"s5fv0kXmQEHm"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["end_station = dff.groupby('end_station_name').agg(station_cnt=('route_cnt', 'sum')).reset_index()"],"metadata":{"id":"zxobliSJQbya"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["end_station = end_station.sort_values(by='station_cnt', ascending=False).head(10)"],"metadata":{"id":"LLAUg0ESQb0j"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["filtered_dff = dff[\n","    (dff['start_station_name'].isin(start_station['start_station_name'])) &\n","    (dff['end_station_name'].isin(end_station['end_station_name']))\n","]"],"metadata":{"id":"u38PBMKAS87J"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["filtered_dff"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":419},"id":"0pI_bZ1mS89S","executionInfo":{"status":"ok","timestamp":1725558562633,"user_tz":240,"elapsed":256,"user":{"displayName":"Wangsheng Wu","userId":"00552226409306193312"}},"outputId":"657cfe99-5ce2-4366-8d75-86bd3a824d36"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["          start_station_name         end_station_name  ride_month  route_cnt\n","533          1 Ave & E 68 St  University Pl & E 14 St           5          1\n","538          1 Ave & E 68 St          W 21 St & 6 Ave           9          1\n","539          1 Ave & E 68 St          W 31 St & 7 Ave           6          1\n","932         11 Ave & W 41 St       Broadway & W 58 St           4          1\n","962         11 Ave & W 41 St          W 21 St & 6 Ave          12          1\n","...                      ...                      ...         ...        ...\n","33792  West St & Chambers St    West St & Chambers St           7          1\n","33793  West St & Chambers St    West St & Chambers St           9          1\n","33794  West St & Chambers St    West St & Chambers St          11          1\n","33795  West St & Chambers St     West St & Liberty St           4          2\n","33796  West St & Chambers St     West St & Liberty St          12          1\n","\n","[67 rows x 4 columns]"],"text/html":["\n","  <div id=\"df-6fee199a-0592-4616-b8cb-21c3fdd2ff69\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>start_station_name</th>\n","      <th>end_station_name</th>\n","      <th>ride_month</th>\n","      <th>route_cnt</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>533</th>\n","      <td>1 Ave &amp; E 68 St</td>\n","      <td>University Pl &amp; E 14 St</td>\n","      <td>5</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>538</th>\n","      <td>1 Ave &amp; E 68 St</td>\n","      <td>W 21 St &amp; 6 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