2-cbp-over-time.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a7b37053-36e3-4b8a-9d91-86d47790c706",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "49256db6-1363-43de-bb25-02fe32d7e992",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"cbp-today.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1e633b68-542b-46b3-ba57-0547ffbd8866",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>Airport</th>\n",
       "      <th>Terminal</th>\n",
       "      <th>date</th>\n",
       "      <th>hour</th>\n",
       "      <th>US Citizen Avg</th>\n",
       "      <th>US Citizen Max</th>\n",
       "      <th>Non-Citizen Avg</th>\n",
       "      <th>Non-Citizen Max</th>\n",
       "      <th>Avg Wait Time</th>\n",
       "      <th>Max Wait Time</th>\n",
       "      <th>Total Passengers</th>\n",
       "      <th>Total Flights</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>JFK</td>\n",
       "      <td>Terminal 1</td>\n",
       "      <td>8/7/2023</td>\n",
       "      <td>1000 - 1100</td>\n",
       "      <td>32</td>\n",
       "      <td>53</td>\n",
       "      <td>29</td>\n",
       "      <td>52</td>\n",
       "      <td>30</td>\n",
       "      <td>53</td>\n",
       "      <td>624</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JFK</td>\n",
       "      <td>Terminal 1</td>\n",
       "      <td>8/7/2023</td>\n",
       "      <td>1100 - 1200</td>\n",
       "      <td>41</td>\n",
       "      <td>91</td>\n",
       "      <td>90</td>\n",
       "      <td>165</td>\n",
       "      <td>72</td>\n",
       "      <td>165</td>\n",
       "      <td>1654</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JFK</td>\n",
       "      <td>Terminal 1</td>\n",
       "      <td>8/7/2023</td>\n",
       "      <td>1300 - 1400</td>\n",
       "      <td>31</td>\n",
       "      <td>102</td>\n",
       "      <td>97</td>\n",
       "      <td>153</td>\n",
       "      <td>73</td>\n",
       "      <td>153</td>\n",
       "      <td>1335</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>JFK</td>\n",
       "      <td>Terminal 1</td>\n",
       "      <td>8/7/2023</td>\n",
       "      <td>1400 - 1500</td>\n",
       "      <td>41</td>\n",
       "      <td>138</td>\n",
       "      <td>110</td>\n",
       "      <td>179</td>\n",
       "      <td>94</td>\n",
       "      <td>179</td>\n",
       "      <td>1017</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>JFK</td>\n",
       "      <td>Terminal 1</td>\n",
       "      <td>8/7/2023</td>\n",
       "      <td>1500 - 1600</td>\n",
       "      <td>61</td>\n",
       "      <td>148</td>\n",
       "      <td>134</td>\n",
       "      <td>171</td>\n",
       "      <td>107</td>\n",
       "      <td>171</td>\n",
       "      <td>748</td>\n",
       "      <td>2</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>JFK</td>\n",
       "      <td>Terminal 8 (American)</td>\n",
       "      <td>8/7/2023</td>\n",
       "      <td>1900 - 2000</td>\n",
       "      <td>34</td>\n",
       "      <td>115</td>\n",
       "      <td>65</td>\n",
       "      <td>116</td>\n",
       "      <td>46</td>\n",
       "      <td>116</td>\n",
       "      <td>1112</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>JFK</td>\n",
       "      <td>Terminal 8 (American)</td>\n",
       "      <td>8/7/2023</td>\n",
       "      <td>2000 - 2100</td>\n",
       "      <td>32</td>\n",
       "      <td>70</td>\n",
       "      <td>68</td>\n",
       "      <td>102</td>\n",
       "      <td>49</td>\n",
       "      <td>102</td>\n",
       "      <td>761</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>JFK</td>\n",
       "      <td>Terminal 8 (American)</td>\n",
       "      <td>8/7/2023</td>\n",
       "      <td>2100 - 2200</td>\n",
       "      <td>26</td>\n",
       "      <td>63</td>\n",
       "      <td>55</td>\n",
       "      <td>69</td>\n",
       "      <td>43</td>\n",
       "      <td>69</td>\n",
       "      <td>234</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>JFK</td>\n",
       "      <td>Terminal 8 (American)</td>\n",
       "      <td>8/7/2023</td>\n",
       "      <td>2200 - 2300</td>\n",
       "      <td>13</td>\n",
       "      <td>55</td>\n",
       "      <td>34</td>\n",
       "      <td>94</td>\n",
       "      <td>25</td>\n",
       "      <td>94</td>\n",
       "      <td>1113</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>JFK</td>\n",
       "      <td>Terminal 8 (American)</td>\n",
       "      <td>8/7/2023</td>\n",
       "      <td>2300 - 0000</td>\n",
       "      <td>21</td>\n",
       "      <td>89</td>\n",
       "      <td>71</td>\n",
       "      <td>97</td>\n",
       "      <td>42</td>\n",
       "      <td>97</td>\n",
       "      <td>517</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>76 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Airport               Terminal      date         hour  US Citizen Avg  \\\n",
       "0      JFK             Terminal 1  8/7/2023  1000 - 1100              32   \n",
       "1      JFK             Terminal 1  8/7/2023  1100 - 1200              41   \n",
       "2      JFK             Terminal 1  8/7/2023  1300 - 1400              31   \n",
       "3      JFK             Terminal 1  8/7/2023  1400 - 1500              41   \n",
       "4      JFK             Terminal 1  8/7/2023  1500 - 1600              61   \n",
       "..     ...                    ...       ...          ...             ...   \n",
       "71     JFK  Terminal 8 (American)  8/7/2023  1900 - 2000              34   \n",
       "72     JFK  Terminal 8 (American)  8/7/2023  2000 - 2100              32   \n",
       "73     JFK  Terminal 8 (American)  8/7/2023  2100 - 2200              26   \n",
       "74     JFK  Terminal 8 (American)  8/7/2023  2200 - 2300              13   \n",
       "75     JFK  Terminal 8 (American)  8/7/2023  2300 - 0000              21   \n",
       "\n",
       "    US Citizen Max  Non-Citizen Avg  Non-Citizen Max  Avg Wait Time  \\\n",
       "0               53               29               52             30   \n",
       "1               91               90              165             72   \n",
       "2              102               97              153             73   \n",
       "3              138              110              179             94   \n",
       "4              148              134              171            107   \n",
       "..             ...              ...              ...            ...   \n",
       "71             115               65              116             46   \n",
       "72              70               68              102             49   \n",
       "73              63               55               69             43   \n",
       "74              55               34               94             25   \n",
       "75              89               71               97             42   \n",
       "\n",
       "    Max Wait Time  Total Passengers  Total Flights  \n",
       "0              53               624              2  \n",
       "1             165              1654              5  \n",
       "2             153              1335              5  \n",
       "3             179              1017              4  \n",
       "4             171               748              2  \n",
       "..            ...               ...            ...  \n",
       "71            116              1112              5  \n",
       "72            102               761              3  \n",
       "73             69               234              1  \n",
       "74             94              1113              4  \n",
       "75             97               517              2  \n",
       "\n",
       "[76 rows x 12 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f20d53c-b8f1-4664-aa02-6db25a2d89c0",
   "metadata": {},
   "source": [
    "If it is the first time, run this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7a523348-766c-43a2-a515-a4b40b3454b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.to_csv('cdp-multiple-days.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4f0f16c-6150-431d-826c-0c0ab5fc6526",
   "metadata": {},
   "source": [
    "After that, run this instead:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c94665c5-1055-4fbb-be9e-4386682b91e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('cdp-multiple-days.csv', mode='a', index=False, header=False)"
   ]
  }
 ],
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