Data_Handling/Concat_CSV_Files.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9b79c3ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import dependencies\n",
    "import pandas as pd\n",
    "import os\n",
    "import datetime as dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "01d68279",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'c:\\\\Users\\\\Ryan\\\\Desktop\\\\GitHub_Repos\\\\citi_bike_tableau\\\\Data_Handling'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get CWD\n",
    "cwd = os.getcwd()\n",
    "cwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2bb993d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "11\n",
      "12\n",
      "01\n",
      "06\n",
      "07\n",
      "08\n"
     ]
    }
   ],
   "source": [
    "# View each filenames month - Filename format is 'YYYY-MM_JC.csv'\n",
    "for file in os.listdir(cwd + \"\\\\Resources\\\\\"):\n",
    "    filename = os.fsdecode(file)\n",
    "    if filename.endswith(\".csv\"):\n",
    "        print(filename.split(\"-\")[1].split(\"_\")[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5ffe98a7",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Create two lists to concat the dfs\n",
    "\n",
    "# One list for winter months\n",
    "# One list for summer months\n",
    "winter_dfs = []\n",
    "summer_dfs = []\n",
    "\n",
    "# Loop through each file in the Resources directory\n",
    "for file in os.listdir(cwd + \"\\\\Resources\\\\\"):\n",
    "    filename = os.fsdecode(file)\n",
    "    if filename.endswith(\".csv\"):\n",
    "        # Check the month of the file name - If it's a winter month, append to the 'winter_dfs' list\n",
    "        if (int(filename.split(\"-\")[1].split(\"_\")[0]) == 11 or int(filename.split(\"-\")[1].split(\"_\")[0]) == 12 or int(filename.split(\"-\")[1].split(\"_\")[0]) == 1):\n",
    "            df = pd.read_csv(cwd+\"\\\\Resources\\\\\"+filename, dtype={'start_station_id':\"string\", \"end_station_id\":\"string\"})\n",
    "            winter_dfs.append(df)\n",
    "        else:\n",
    "            # If its not a winter month - append to the 'summer_dfs' list \n",
    "            df = pd.read_csv(cwd+\"\\\\Resources\\\\\"+filename, dtype={'start_station_id':\"string\", \"end_station_id\":\"string\"})\n",
    "            summer_dfs.append(df)\n",
    "    else:\n",
    "        # If the file is not a csv, continue to the next file\n",
    "        continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6251d084",
   "metadata": {},
   "outputs": [
    {
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       "  <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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>37BE5FCB1A385CDA</td>\n",
       "      <td>classic_bike</td>\n",
       "      <td>2023-06-27 16:06:27</td>\n",
       "      <td>2023-06-27 16:10:27</td>\n",
       "      <td>Hilltop</td>\n",
       "      <td>JC019</td>\n",
       "      <td>Christ Hospital</td>\n",
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       "      <td>-74.057468</td>\n",
       "      <td>40.734786</td>\n",
       "      <td>-74.050444</td>\n",
       "      <td>casual</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9C96B4C6CBBB31AD</td>\n",
       "      <td>classic_bike</td>\n",
       "      <td>2023-06-24 10:46:58</td>\n",
       "      <td>2023-06-24 10:55:27</td>\n",
       "      <td>Baldwin at Montgomery</td>\n",
       "      <td>JC020</td>\n",
       "      <td>Hamilton Park</td>\n",
       "      <td>JC009</td>\n",
       "      <td>40.723473</td>\n",
       "      <td>-74.064338</td>\n",
       "      <td>40.727596</td>\n",
       "      <td>-74.044247</td>\n",
       "      <td>member</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C91293605D4BEC07</td>\n",
       "      <td>electric_bike</td>\n",
       "      <td>2023-06-04 20:30:13</td>\n",
       "      <td>2023-06-04 20:34:31</td>\n",
       "      <td>Hilltop</td>\n",
       "      <td>JC019</td>\n",
       "      <td>Brunswick St</td>\n",
       "      <td>JC023</td>\n",
       "      <td>40.731169</td>\n",
       "      <td>-74.057574</td>\n",
       "      <td>40.724176</td>\n",
       "      <td>-74.050656</td>\n",
       "      <td>member</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2920063442116A46</td>\n",
       "      <td>classic_bike</td>\n",
       "      <td>2023-06-08 19:10:06</td>\n",
       "      <td>2023-06-08 19:13:05</td>\n",
       "      <td>Baldwin at Montgomery</td>\n",
       "      <td>JC020</td>\n",
       "      <td>Astor Place</td>\n",
       "      <td>JC077</td>\n",
       "      <td>40.723499</td>\n",
       "      <td>-74.064335</td>\n",
       "      <td>40.719282</td>\n",
       "      <td>-74.071262</td>\n",
       "      <td>member</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>E205FD8C18BA263A</td>\n",
       "      <td>classic_bike</td>\n",
       "      <td>2023-06-23 18:53:51</td>\n",
       "      <td>2023-06-23 19:17:50</td>\n",
       "      <td>Baldwin at Montgomery</td>\n",
       "      <td>JC020</td>\n",
       "      <td>Adams St &amp; 11 St</td>\n",
       "      <td>HB507</td>\n",
       "      <td>40.723511</td>\n",
       "      <td>-74.064277</td>\n",
       "      <td>40.750916</td>\n",
       "      <td>-74.033541</td>\n",
       "      <td>member</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "            ride_id  rideable_type           started_at             ended_at  \\\n",
       "0  37BE5FCB1A385CDA   classic_bike  2023-06-27 16:06:27  2023-06-27 16:10:27   \n",
       "1  9C96B4C6CBBB31AD   classic_bike  2023-06-24 10:46:58  2023-06-24 10:55:27   \n",
       "2  C91293605D4BEC07  electric_bike  2023-06-04 20:30:13  2023-06-04 20:34:31   \n",
       "3  2920063442116A46   classic_bike  2023-06-08 19:10:06  2023-06-08 19:13:05   \n",
       "4  E205FD8C18BA263A   classic_bike  2023-06-23 18:53:51  2023-06-23 19:17:50   \n",
       "\n",
       "      start_station_name start_station_id  end_station_name end_station_id  \\\n",
       "0                Hilltop            JC019   Christ Hospital          JC034   \n",
       "1  Baldwin at Montgomery            JC020     Hamilton Park          JC009   \n",
       "2                Hilltop            JC019      Brunswick St          JC023   \n",
       "3  Baldwin at Montgomery            JC020       Astor Place          JC077   \n",
       "4  Baldwin at Montgomery            JC020  Adams St & 11 St          HB507   \n",
       "\n",
       "   start_lat  start_lng    end_lat    end_lng member_casual  \n",
       "0  40.731115 -74.057468  40.734786 -74.050444        casual  \n",
       "1  40.723473 -74.064338  40.727596 -74.044247        member  \n",
       "2  40.731169 -74.057574  40.724176 -74.050656        member  \n",
       "3  40.723499 -74.064335  40.719282 -74.071262        member  \n",
       "4  40.723511 -74.064277  40.750916 -74.033541        member  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
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    }
   ],
   "source": [
    "# Concat the summer months into one df\n",
    "summer_df = pd.concat(summer_dfs)\n",
    "\n",
    "# Reset the index to remove duplicate values\n",
    "summer_df = summer_df.reset_index(drop=True)\n",
    "\n",
    "# Preview the df\n",
    "summer_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b49a5682",
   "metadata": {},
   "outputs": [
    {
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       "  <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",
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       "      <th>start_lng</th>\n",
       "      <th>end_lat</th>\n",
       "      <th>end_lng</th>\n",
       "      <th>member_casual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7B06EEA21608591A</td>\n",
       "      <td>classic_bike</td>\n",
       "      <td>2022-11-12 14:47:21</td>\n",
       "      <td>2022-11-12 14:58:55</td>\n",
       "      <td>Newport PATH</td>\n",
       "      <td>JC066</td>\n",
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       "      <td>casual</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B22A3E8765F1E165</td>\n",
       "      <td>classic_bike</td>\n",
       "      <td>2022-11-30 08:29:53</td>\n",
       "      <td>2022-11-30 08:45:56</td>\n",
       "      <td>Newport PATH</td>\n",
       "      <td>JC066</td>\n",
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       "      <td>40.727216</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CFB2EB1663C02BB6</td>\n",
       "      <td>electric_bike</td>\n",
       "      <td>2022-11-09 08:28:30</td>\n",
       "      <td>2022-11-09 08:44:50</td>\n",
       "      <td>Newport PATH</td>\n",
       "      <td>JC066</td>\n",
       "      <td>7 St &amp; Monroe St</td>\n",
       "      <td>HB304</td>\n",
       "      <td>40.727224</td>\n",
       "      <td>-74.033759</td>\n",
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       "      <td>-74.037977</td>\n",
       "      <td>member</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>85700816DAAE1C36</td>\n",
       "      <td>electric_bike</td>\n",
       "      <td>2022-11-30 14:48:11</td>\n",
       "      <td>2022-11-30 14:58:10</td>\n",
       "      <td>Newport PATH</td>\n",
       "      <td>JC066</td>\n",
       "      <td>7 St &amp; Monroe St</td>\n",
       "      <td>HB304</td>\n",
       "      <td>40.727224</td>\n",
       "      <td>-74.033759</td>\n",
       "      <td>40.746413</td>\n",
       "      <td>-74.037977</td>\n",
       "      <td>member</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>009EBB1F54C5947E</td>\n",
       "      <td>electric_bike</td>\n",
       "      <td>2022-11-10 18:14:33</td>\n",
       "      <td>2022-11-10 18:23:08</td>\n",
       "      <td>Newport PATH</td>\n",
       "      <td>JC066</td>\n",
       "      <td>7 St &amp; Monroe St</td>\n",
       "      <td>HB304</td>\n",
       "      <td>40.727224</td>\n",
       "      <td>-74.033759</td>\n",
       "      <td>40.746413</td>\n",
       "      <td>-74.037977</td>\n",
       "      <td>member</td>\n",
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      "text/plain": [
       "            ride_id  rideable_type           started_at             ended_at  \\\n",
       "0  7B06EEA21608591A   classic_bike  2022-11-12 14:47:21  2022-11-12 14:58:55   \n",
       "1  B22A3E8765F1E165   classic_bike  2022-11-30 08:29:53  2022-11-30 08:45:56   \n",
       "2  CFB2EB1663C02BB6  electric_bike  2022-11-09 08:28:30  2022-11-09 08:44:50   \n",
       "3  85700816DAAE1C36  electric_bike  2022-11-30 14:48:11  2022-11-30 14:58:10   \n",
       "4  009EBB1F54C5947E  electric_bike  2022-11-10 18:14:33  2022-11-10 18:23:08   \n",
       "\n",
       "  start_station_name start_station_id  end_station_name end_station_id  \\\n",
       "0       Newport PATH            JC066  7 St & Monroe St          HB304   \n",
       "1       Newport PATH            JC066  7 St & Monroe St          HB304   \n",
       "2       Newport PATH            JC066  7 St & Monroe St          HB304   \n",
       "3       Newport PATH            JC066  7 St & Monroe St          HB304   \n",
       "4       Newport PATH            JC066  7 St & Monroe St          HB304   \n",
       "\n",
       "   start_lat  start_lng    end_lat    end_lng member_casual  \n",
       "0  40.727146 -74.033620  40.746413 -74.037977        casual  \n",
       "1  40.727216 -74.033609  40.746413 -74.037977        member  \n",
       "2  40.727224 -74.033759  40.746413 -74.037977        member  \n",
       "3  40.727224 -74.033759  40.746413 -74.037977        member  \n",
       "4  40.727224 -74.033759  40.746413 -74.037977        member  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Concat the winter months into one df\n",
    "winter_df = pd.concat(winter_dfs)\n",
    "\n",
    "# Reset the index to remove duplicate values\n",
    "winter_df = winter_df.reset_index(drop=True)\n",
    "\n",
    "# Preview the df\n",
    "winter_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ecfc71b8-9b06-4890-8f08-6ab0bad0975e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 315658 entries, 0 to 315657\n",
      "Data columns (total 13 columns):\n",
      " #   Column              Non-Null Count   Dtype         \n",
      "---  ------              --------------   -----         \n",
      " 0   ride_id             315658 non-null  object        \n",
      " 1   rideable_type       315658 non-null  object        \n",
      " 2   started_at          315658 non-null  datetime64[ns]\n",
      " 3   ended_at            315658 non-null  datetime64[ns]\n",
      " 4   start_station_name  315596 non-null  object        \n",
      " 5   start_station_id    315596 non-null  string        \n",
      " 6   end_station_name    314579 non-null  object        \n",
      " 7   end_station_id      314579 non-null  string        \n",
      " 8   start_lat           315658 non-null  float64       \n",
      " 9   start_lng           315658 non-null  float64       \n",
      " 10  end_lat             315328 non-null  float64       \n",
      " 11  end_lng             315328 non-null  float64       \n",
      " 12  member_casual       315658 non-null  object        \n",
      "dtypes: datetime64[ns](2), float64(4), object(5), string(2)\n",
      "memory usage: 31.3+ MB\n",
      "None\n",
      "--------------------------------------------------\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 177369 entries, 0 to 177368\n",
      "Data columns (total 13 columns):\n",
      " #   Column              Non-Null Count   Dtype         \n",
      "---  ------              --------------   -----         \n",
      " 0   ride_id             177369 non-null  object        \n",
      " 1   rideable_type       177369 non-null  object        \n",
      " 2   started_at          177369 non-null  datetime64[ns]\n",
      " 3   ended_at            177369 non-null  datetime64[ns]\n",
      " 4   start_station_name  177359 non-null  object        \n",
      " 5   start_station_id    177359 non-null  string        \n",
      " 6   end_station_name    176680 non-null  object        \n",
      " 7   end_station_id      176680 non-null  string        \n",
      " 8   start_lat           177369 non-null  float64       \n",
      " 9   start_lng           177369 non-null  float64       \n",
      " 10  end_lat             177134 non-null  float64       \n",
      " 11  end_lng             177134 non-null  float64       \n",
      " 12  member_casual       177369 non-null  object        \n",
      "dtypes: datetime64[ns](2), float64(4), object(5), string(2)\n",
      "memory usage: 17.6+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "# Convert start and end date/time to correct dtype\n",
    "summer_df[[\"started_at\",\"ended_at\"]] = summer_df[[\"started_at\",\"ended_at\"]].astype(\"datetime64[ns]\", errors=\"raise\")\n",
    "winter_df[[\"started_at\",\"ended_at\"]] = winter_df[[\"started_at\",\"ended_at\"]].astype(\"datetime64[ns]\", errors=\"raise\")\n",
    "\n",
    "# Check the dtypes are correct\n",
    "print(summer_df.info())\n",
    "print(\"-\" * 50)\n",
    "print(winter_df.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cf704d0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add a column to join the weather data to in Tableau\n",
    "summer_df['weather_join'] = summer_df['started_at'].dt.strftime(\"%Y-%m-%d %H:00:00\")\n",
    "winter_df['weather_join'] = winter_df['started_at'].dt.strftime(\"%Y-%m-%d %H:00:00\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c926dbc6",
   "metadata": {},
   "outputs": [
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       "        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>weather_join</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>37BE5FCB1A385CDA</td>\n",
       "      <td>classic_bike</td>\n",
       "      <td>2023-06-27 16:06:27</td>\n",
       "      <td>2023-06-27 16:10:27</td>\n",
       "      <td>Hilltop</td>\n",
       "      <td>JC019</td>\n",
       "      <td>Christ Hospital</td>\n",
       "      <td>JC034</td>\n",
       "      <td>40.731115</td>\n",
       "      <td>-74.057468</td>\n",
       "      <td>40.734786</td>\n",
       "      <td>-74.050444</td>\n",
       "      <td>casual</td>\n",
       "      <td>2023-06-27 16:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9C96B4C6CBBB31AD</td>\n",
       "      <td>classic_bike</td>\n",
       "      <td>2023-06-24 10:46:58</td>\n",
       "      <td>2023-06-24 10:55:27</td>\n",
       "      <td>Baldwin at Montgomery</td>\n",
       "      <td>JC020</td>\n",
       "      <td>Hamilton Park</td>\n",
       "      <td>JC009</td>\n",
       "      <td>40.723473</td>\n",
       "      <td>-74.064338</td>\n",
       "      <td>40.727596</td>\n",
       "      <td>-74.044247</td>\n",
       "      <td>member</td>\n",
       "      <td>2023-06-24 10:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C91293605D4BEC07</td>\n",
       "      <td>electric_bike</td>\n",
       "      <td>2023-06-04 20:30:13</td>\n",
       "      <td>2023-06-04 20:34:31</td>\n",
       "      <td>Hilltop</td>\n",
       "      <td>JC019</td>\n",
       "      <td>Brunswick St</td>\n",
       "      <td>JC023</td>\n",
       "      <td>40.731169</td>\n",
       "      <td>-74.057574</td>\n",
       "      <td>40.724176</td>\n",
       "      <td>-74.050656</td>\n",
       "      <td>member</td>\n",
       "      <td>2023-06-04 20:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2920063442116A46</td>\n",
       "      <td>classic_bike</td>\n",
       "      <td>2023-06-08 19:10:06</td>\n",
       "      <td>2023-06-08 19:13:05</td>\n",
       "      <td>Baldwin at Montgomery</td>\n",
       "      <td>JC020</td>\n",
       "      <td>Astor Place</td>\n",
       "      <td>JC077</td>\n",
       "      <td>40.723499</td>\n",
       "      <td>-74.064335</td>\n",
       "      <td>40.719282</td>\n",
       "      <td>-74.071262</td>\n",
       "      <td>member</td>\n",
       "      <td>2023-06-08 19:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>E205FD8C18BA263A</td>\n",
       "      <td>classic_bike</td>\n",
       "      <td>2023-06-23 18:53:51</td>\n",
       "      <td>2023-06-23 19:17:50</td>\n",
       "      <td>Baldwin at Montgomery</td>\n",
       "      <td>JC020</td>\n",
       "      <td>Adams St &amp; 11 St</td>\n",
       "      <td>HB507</td>\n",
       "      <td>40.723511</td>\n",
       "      <td>-74.064277</td>\n",
       "      <td>40.750916</td>\n",
       "      <td>-74.033541</td>\n",
       "      <td>member</td>\n",
       "      <td>2023-06-23 18:00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ride_id  rideable_type          started_at            ended_at  \\\n",
       "0  37BE5FCB1A385CDA   classic_bike 2023-06-27 16:06:27 2023-06-27 16:10:27   \n",
       "1  9C96B4C6CBBB31AD   classic_bike 2023-06-24 10:46:58 2023-06-24 10:55:27   \n",
       "2  C91293605D4BEC07  electric_bike 2023-06-04 20:30:13 2023-06-04 20:34:31   \n",
       "3  2920063442116A46   classic_bike 2023-06-08 19:10:06 2023-06-08 19:13:05   \n",
       "4  E205FD8C18BA263A   classic_bike 2023-06-23 18:53:51 2023-06-23 19:17:50   \n",
       "\n",
       "      start_station_name start_station_id  end_station_name end_station_id  \\\n",
       "0                Hilltop            JC019   Christ Hospital          JC034   \n",
       "1  Baldwin at Montgomery            JC020     Hamilton Park          JC009   \n",
       "2                Hilltop            JC019      Brunswick St          JC023   \n",
       "3  Baldwin at Montgomery            JC020       Astor Place          JC077   \n",
       "4  Baldwin at Montgomery            JC020  Adams St & 11 St          HB507   \n",
       "\n",
       "   start_lat  start_lng    end_lat    end_lng member_casual  \\\n",
       "0  40.731115 -74.057468  40.734786 -74.050444        casual   \n",
       "1  40.723473 -74.064338  40.727596 -74.044247        member   \n",
       "2  40.731169 -74.057574  40.724176 -74.050656        member   \n",
       "3  40.723499 -74.064335  40.719282 -74.071262        member   \n",
       "4  40.723511 -74.064277  40.750916 -74.033541        member   \n",
       "\n",
       "          weather_join  \n",
       "0  2023-06-27 16:00:00  \n",
       "1  2023-06-24 10:00:00  \n",
       "2  2023-06-04 20:00:00  \n",
       "3  2023-06-08 19:00:00  \n",
       "4  2023-06-23 18:00:00  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the `summer_df` DataFrame\n",
    "summer_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1cb6aa30",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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>weather_join</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7B06EEA21608591A</td>\n",
       "      <td>classic_bike</td>\n",
       "      <td>2022-11-12 14:47:21</td>\n",
       "      <td>2022-11-12 14:58:55</td>\n",
       "      <td>Newport PATH</td>\n",
       "      <td>JC066</td>\n",
       "      <td>7 St &amp; Monroe St</td>\n",
       "      <td>HB304</td>\n",
       "      <td>40.727146</td>\n",
       "      <td>-74.033620</td>\n",
       "      <td>40.746413</td>\n",
       "      <td>-74.037977</td>\n",
       "      <td>casual</td>\n",
       "      <td>2022-11-12 14:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B22A3E8765F1E165</td>\n",
       "      <td>classic_bike</td>\n",
       "      <td>2022-11-30 08:29:53</td>\n",
       "      <td>2022-11-30 08:45:56</td>\n",
       "      <td>Newport PATH</td>\n",
       "      <td>JC066</td>\n",
       "      <td>7 St &amp; Monroe St</td>\n",
       "      <td>HB304</td>\n",
       "      <td>40.727216</td>\n",
       "      <td>-74.033609</td>\n",
       "      <td>40.746413</td>\n",
       "      <td>-74.037977</td>\n",
       "      <td>member</td>\n",
       "      <td>2022-11-30 08:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CFB2EB1663C02BB6</td>\n",
       "      <td>electric_bike</td>\n",
       "      <td>2022-11-09 08:28:30</td>\n",
       "      <td>2022-11-09 08:44:50</td>\n",
       "      <td>Newport PATH</td>\n",
       "      <td>JC066</td>\n",
       "      <td>7 St &amp; Monroe St</td>\n",
       "      <td>HB304</td>\n",
       "      <td>40.727224</td>\n",
       "      <td>-74.033759</td>\n",
       "      <td>40.746413</td>\n",
       "      <td>-74.037977</td>\n",
       "      <td>member</td>\n",
       "      <td>2022-11-09 08:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>85700816DAAE1C36</td>\n",
       "      <td>electric_bike</td>\n",
       "      <td>2022-11-30 14:48:11</td>\n",
       "      <td>2022-11-30 14:58:10</td>\n",
       "      <td>Newport PATH</td>\n",
       "      <td>JC066</td>\n",
       "      <td>7 St &amp; Monroe St</td>\n",
       "      <td>HB304</td>\n",
       "      <td>40.727224</td>\n",
       "      <td>-74.033759</td>\n",
       "      <td>40.746413</td>\n",
       "      <td>-74.037977</td>\n",
       "      <td>member</td>\n",
       "      <td>2022-11-30 14:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>009EBB1F54C5947E</td>\n",
       "      <td>electric_bike</td>\n",
       "      <td>2022-11-10 18:14:33</td>\n",
       "      <td>2022-11-10 18:23:08</td>\n",
       "      <td>Newport PATH</td>\n",
       "      <td>JC066</td>\n",
       "      <td>7 St &amp; Monroe St</td>\n",
       "      <td>HB304</td>\n",
       "      <td>40.727224</td>\n",
       "      <td>-74.033759</td>\n",
       "      <td>40.746413</td>\n",
       "      <td>-74.037977</td>\n",
       "      <td>member</td>\n",
       "      <td>2022-11-10 18:00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ride_id  rideable_type          started_at            ended_at  \\\n",
       "0  7B06EEA21608591A   classic_bike 2022-11-12 14:47:21 2022-11-12 14:58:55   \n",
       "1  B22A3E8765F1E165   classic_bike 2022-11-30 08:29:53 2022-11-30 08:45:56   \n",
       "2  CFB2EB1663C02BB6  electric_bike 2022-11-09 08:28:30 2022-11-09 08:44:50   \n",
       "3  85700816DAAE1C36  electric_bike 2022-11-30 14:48:11 2022-11-30 14:58:10   \n",
       "4  009EBB1F54C5947E  electric_bike 2022-11-10 18:14:33 2022-11-10 18:23:08   \n",
       "\n",
       "  start_station_name start_station_id  end_station_name end_station_id  \\\n",
       "0       Newport PATH            JC066  7 St & Monroe St          HB304   \n",
       "1       Newport PATH            JC066  7 St & Monroe St          HB304   \n",
       "2       Newport PATH            JC066  7 St & Monroe St          HB304   \n",
       "3       Newport PATH            JC066  7 St & Monroe St          HB304   \n",
       "4       Newport PATH            JC066  7 St & Monroe St          HB304   \n",
       "\n",
       "   start_lat  start_lng    end_lat    end_lng member_casual  \\\n",
       "0  40.727146 -74.033620  40.746413 -74.037977        casual   \n",
       "1  40.727216 -74.033609  40.746413 -74.037977        member   \n",
       "2  40.727224 -74.033759  40.746413 -74.037977        member   \n",
       "3  40.727224 -74.033759  40.746413 -74.037977        member   \n",
       "4  40.727224 -74.033759  40.746413 -74.037977        member   \n",
       "\n",
       "          weather_join  \n",
       "0  2022-11-12 14:00:00  \n",
       "1  2022-11-30 08:00:00  \n",
       "2  2022-11-09 08:00:00  \n",
       "3  2022-11-30 14:00:00  \n",
       "4  2022-11-10 18:00:00  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the `winter_df` DataFrame\n",
    "winter_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "80e09729",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Output the dataframes to CSV files\n",
    "summer_df.to_csv(\"Outputs/summer_df.csv\", index=False)\n",
    "winter_df.to_csv(\"Outputs/winter_df.csv\", index=False)"
   ]
  }
 ],
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