bigquery2dataframe_flights.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "query=\"\"\"\n",
    "SELECT\n",
    "  departure_delay,\n",
    "  COUNT(1) AS num_flights,\n",
    "  APPROX_QUANTILES(arrival_delay, 10) AS arrival_delay_deciles\n",
    "FROM\n",
    "  `bigquery-samples.airline_ontime_data.flights`\n",
    "GROUP BY\n",
    "  departure_delay\n",
    "HAVING\n",
    "  num_flights > 100\n",
    "ORDER BY\n",
    "  departure_delay ASC\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "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>departure_delay</th>\n",
       "      <th>num_flights</th>\n",
       "      <th>arrival_delay_deciles</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-37.0</td>\n",
       "      <td>107</td>\n",
       "      <td>[-66.0, -44.0, -41.0, -35.0, -30.0, -23.0, -17...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-36.0</td>\n",
       "      <td>139</td>\n",
       "      <td>[-74.0, -43.0, -39.0, -37.0, -32.0, -25.0, -18...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-35.0</td>\n",
       "      <td>191</td>\n",
       "      <td>[-68.0, -45.0, -40.0, -36.0, -28.0, -19.0, -14...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-34.0</td>\n",
       "      <td>195</td>\n",
       "      <td>[-58.0, -44.0, -40.0, -35.0, -30.0, -25.0, -19...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-33.0</td>\n",
       "      <td>227</td>\n",
       "      <td>[-59.0, -43.0, -39.0, -36.0, -32.0, -28.0, -20...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   departure_delay  num_flights  \\\n",
       "0            -37.0          107   \n",
       "1            -36.0          139   \n",
       "2            -35.0          191   \n",
       "3            -34.0          195   \n",
       "4            -33.0          227   \n",
       "\n",
       "                               arrival_delay_deciles  \n",
       "0  [-66.0, -44.0, -41.0, -35.0, -30.0, -23.0, -17...  \n",
       "1  [-74.0, -43.0, -39.0, -37.0, -32.0, -25.0, -18...  \n",
       "2  [-68.0, -45.0, -40.0, -36.0, -28.0, -19.0, -14...  \n",
       "3  [-58.0, -44.0, -40.0, -35.0, -30.0, -25.0, -19...  \n",
       "4  [-59.0, -43.0, -39.0, -36.0, -32.0, -28.0, -20...  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import google.datalab.bigquery as bq\n",
    "df = bq.Query(query).execute().result().to_dataframe()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        0      1      2      3      4      5      6      7      8      9   \\\n",
      "0    -66.0  -44.0  -41.0  -35.0  -30.0  -23.0  -17.0  -12.0   -3.0    6.0   \n",
      "1    -74.0  -43.0  -39.0  -37.0  -32.0  -25.0  -18.0  -14.0   -7.0    2.0   \n",
      "2    -68.0  -45.0  -40.0  -36.0  -28.0  -19.0  -14.0   -8.0   -4.0    3.0   \n",
      "3    -58.0  -44.0  -40.0  -35.0  -30.0  -25.0  -19.0  -14.0   -8.0    2.0   \n",
      "4    -59.0  -43.0  -39.0  -36.0  -32.0  -28.0  -20.0  -14.0   -7.0    5.0   \n",
      "5    -58.0  -44.0  -38.0  -35.0  -31.0  -28.0  -22.0  -13.0   -5.0    4.0   \n",
      "6    -58.0  -42.0  -37.0  -34.0  -31.0  -27.0  -22.0  -13.0   -7.0   -1.0   \n",
      "7    -90.0  -44.0  -37.0  -33.0  -29.0  -23.0  -18.0  -11.0   -5.0    6.0   \n",
      "8    -53.0  -39.0  -35.0  -32.0  -29.0  -26.0  -21.0  -13.0   -6.0    2.0   \n",
      "9    -54.0  -39.0  -34.0  -31.0  -29.0  -25.0  -21.0  -14.0   -7.0    2.0   \n",
      "10   -82.0  -39.0  -34.0  -31.0  -28.0  -25.0  -20.0  -15.0   -9.0    1.0   \n",
      "11   -86.0  -37.0  -33.0  -30.0  -28.0  -24.0  -21.0  -17.0  -10.0    0.0   \n",
      "12   -65.0  -38.0  -33.0  -30.0  -28.0  -25.0  -22.0  -17.0  -11.0   -2.0   \n",
      "13   -60.0  -37.0  -33.0  -30.0  -27.0  -25.0  -22.0  -18.0  -12.0   -3.0   \n",
      "14   -68.0  -36.0  -32.0  -29.0  -27.0  -24.0  -22.0  -18.0  -12.0   -4.0   \n",
      "15   -73.0  -35.0  -31.0  -28.0  -26.0  -23.0  -21.0  -17.0  -12.0   -4.0   \n",
      "16   -80.0  -34.0  -30.0  -27.0  -25.0  -23.0  -20.0  -17.0  -13.0   -5.0   \n",
      "17   -70.0  -34.0  -30.0  -26.0  -24.0  -22.0  -19.0  -16.0  -11.0   -5.0   \n",
      "18  -157.0  -33.0  -29.0  -26.0  -23.0  -21.0  -18.0  -15.0  -11.0   -4.0   \n",
      "19   -80.0  -32.0  -28.0  -25.0  -22.0  -20.0  -18.0  -14.0  -10.0   -4.0   \n",
      "20   -97.0  -31.0  -27.0  -24.0  -21.0  -19.0  -17.0  -14.0  -10.0   -3.0   \n",
      "21   -88.0  -30.0  -26.0  -23.0  -20.0  -18.0  -16.0  -13.0   -9.0   -3.0   \n",
      "22   -90.0  -30.0  -25.0  -22.0  -19.0  -17.0  -14.0  -12.0   -8.0   -2.0   \n",
      "23   -86.0  -28.0  -24.0  -21.0  -19.0  -16.0  -14.0  -11.0   -7.0   -1.0   \n",
      "24   -80.0  -27.0  -23.0  -20.0  -18.0  -15.0  -13.0  -10.0   -6.0    0.0   \n",
      "25   -92.0  -27.0  -22.0  -19.0  -17.0  -14.0  -12.0   -9.0   -5.0    1.0   \n",
      "26   -94.0  -26.0  -21.0  -18.0  -16.0  -14.0  -11.0   -8.0   -5.0    2.0   \n",
      "27  -129.0  -25.0  -20.0  -18.0  -15.0  -13.0  -10.0   -7.0   -4.0    2.0   \n",
      "28   -93.0  -24.0  -20.0  -17.0  -14.0  -12.0   -9.0   -7.0   -3.0    3.0   \n",
      "29   -88.0  -23.0  -19.0  -16.0  -13.0  -11.0   -9.0   -6.0   -2.0    4.0   \n",
      "..     ...    ...    ...    ...    ...    ...    ...    ...    ...    ...   \n",
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      "483  412.0  423.0  430.0  434.0  439.0  441.0  445.0  450.0  454.0  476.0   \n",
      "484  392.0  424.0  430.0  437.0  440.0  443.0  445.0  449.0  456.0  465.0   \n",
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      "494  412.0  438.0  444.0  447.0  450.0  454.0  458.0  464.0  468.0  478.0   \n",
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      "496  411.0  438.0  443.0  449.0  453.0  455.0  460.0  465.0  471.0  482.0   \n",
      "497  423.0  436.0  444.0  450.0  453.0  457.0  460.0  465.0  468.0  481.0   \n",
      "498  427.0  440.0  447.0  451.0  453.0  457.0  462.0  469.0  478.0  496.0   \n",
      "499  428.0  440.0  448.0  452.0  457.0  462.0  466.0  468.0  478.0  495.0   \n",
      "500  415.0  443.0  449.0  454.0  459.0  463.0  466.0  469.0  475.0  484.0   \n",
      "501  425.0  444.0  450.0  454.0  457.0  460.0  464.0  467.0  473.0  483.0   \n",
      "502  432.0  445.0  451.0  455.0  460.0  463.0  468.0  472.0  476.0  484.0   \n",
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      "504  435.0  455.0  459.0  462.0  466.0  469.0  473.0  478.0  487.0  495.0   \n",
      "505  423.0  455.0  463.0  467.0  473.0  475.0  479.0  485.0  493.0  498.0   \n",
      "506  373.0  461.0  469.0  472.0  476.0  480.0  485.0  489.0  498.0  510.0   \n",
      "507  286.0  470.0  478.0  481.0  485.0  489.0  494.0  497.0  504.0  512.0   \n",
      "\n",
      "         10  \n",
      "0      33.0  \n",
      "1      49.0  \n",
      "2      85.0  \n",
      "3      39.0  \n",
      "4      25.0  \n",
      "5     124.0  \n",
      "6     104.0  \n",
      "7      80.0  \n",
      "8      71.0  \n",
      "9      72.0  \n",
      "10    104.0  \n",
      "11    135.0  \n",
      "12     75.0  \n",
      "13    106.0  \n",
      "14    148.0  \n",
      "15    134.0  \n",
      "16     68.0  \n",
      "17    130.0  \n",
      "18   1416.0  \n",
      "19    186.0  \n",
      "20    149.0  \n",
      "21    169.0  \n",
      "22    910.0  \n",
      "23    823.0  \n",
      "24    205.0  \n",
      "25   1428.0  \n",
      "26    317.0  \n",
      "27   1433.0  \n",
      "28   1433.0  \n",
      "29    505.0  \n",
      "..      ...  \n",
      "478   610.0  \n",
      "479   582.0  \n",
      "480   506.0  \n",
      "481   566.0  \n",
      "482   527.0  \n",
      "483   521.0  \n",
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      "489   564.0  \n",
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      "492   616.0  \n",
      "493   537.0  \n",
      "494   569.0  \n",
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      "497   524.0  \n",
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      "500   645.0  \n",
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      "502   676.0  \n",
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      "505   611.0  \n",
      "506   670.0  \n",
      "507   553.0  \n",
      "\n",
      "[508 rows x 11 columns]\n",
      "        0%    10%    20%    30%    40%    50%    60%    70%    80%    90%  \\\n",
      "0    -66.0  -44.0  -41.0  -35.0  -30.0  -23.0  -17.0  -12.0   -3.0    6.0   \n",
      "1    -74.0  -43.0  -39.0  -37.0  -32.0  -25.0  -18.0  -14.0   -7.0    2.0   \n",
      "2    -68.0  -45.0  -40.0  -36.0  -28.0  -19.0  -14.0   -8.0   -4.0    3.0   \n",
      "3    -58.0  -44.0  -40.0  -35.0  -30.0  -25.0  -19.0  -14.0   -8.0    2.0   \n",
      "4    -59.0  -43.0  -39.0  -36.0  -32.0  -28.0  -20.0  -14.0   -7.0    5.0   \n",
      "5    -58.0  -44.0  -38.0  -35.0  -31.0  -28.0  -22.0  -13.0   -5.0    4.0   \n",
      "6    -58.0  -42.0  -37.0  -34.0  -31.0  -27.0  -22.0  -13.0   -7.0   -1.0   \n",
      "7    -90.0  -44.0  -37.0  -33.0  -29.0  -23.0  -18.0  -11.0   -5.0    6.0   \n",
      "8    -53.0  -39.0  -35.0  -32.0  -29.0  -26.0  -21.0  -13.0   -6.0    2.0   \n",
      "9    -54.0  -39.0  -34.0  -31.0  -29.0  -25.0  -21.0  -14.0   -7.0    2.0   \n",
      "10   -82.0  -39.0  -34.0  -31.0  -28.0  -25.0  -20.0  -15.0   -9.0    1.0   \n",
      "11   -86.0  -37.0  -33.0  -30.0  -28.0  -24.0  -21.0  -17.0  -10.0    0.0   \n",
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      "13   -60.0  -37.0  -33.0  -30.0  -27.0  -25.0  -22.0  -18.0  -12.0   -3.0   \n",
      "14   -68.0  -36.0  -32.0  -29.0  -27.0  -24.0  -22.0  -18.0  -12.0   -4.0   \n",
      "15   -73.0  -35.0  -31.0  -28.0  -26.0  -23.0  -21.0  -17.0  -12.0   -4.0   \n",
      "16   -80.0  -34.0  -30.0  -27.0  -25.0  -23.0  -20.0  -17.0  -13.0   -5.0   \n",
      "17   -70.0  -34.0  -30.0  -26.0  -24.0  -22.0  -19.0  -16.0  -11.0   -5.0   \n",
      "18  -157.0  -33.0  -29.0  -26.0  -23.0  -21.0  -18.0  -15.0  -11.0   -4.0   \n",
      "19   -80.0  -32.0  -28.0  -25.0  -22.0  -20.0  -18.0  -14.0  -10.0   -4.0   \n",
      "20   -97.0  -31.0  -27.0  -24.0  -21.0  -19.0  -17.0  -14.0  -10.0   -3.0   \n",
      "21   -88.0  -30.0  -26.0  -23.0  -20.0  -18.0  -16.0  -13.0   -9.0   -3.0   \n",
      "22   -90.0  -30.0  -25.0  -22.0  -19.0  -17.0  -14.0  -12.0   -8.0   -2.0   \n",
      "23   -86.0  -28.0  -24.0  -21.0  -19.0  -16.0  -14.0  -11.0   -7.0   -1.0   \n",
      "24   -80.0  -27.0  -23.0  -20.0  -18.0  -15.0  -13.0  -10.0   -6.0    0.0   \n",
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      "28   -93.0  -24.0  -20.0  -17.0  -14.0  -12.0   -9.0   -7.0   -3.0    3.0   \n",
      "29   -88.0  -23.0  -19.0  -16.0  -13.0  -11.0   -9.0   -6.0   -2.0    4.0   \n",
      "..     ...    ...    ...    ...    ...    ...    ...    ...    ...    ...   \n",
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      "486  352.0  428.0  433.0  438.0  441.0  444.0  446.0  450.0  453.0  461.0   \n",
      "487  368.0  424.0  433.0  438.0  442.0  447.0  450.0  455.0  461.0  468.0   \n",
      "488  407.0  430.0  435.0  438.0  441.0  443.0  446.0  449.0  457.0  474.0   \n",
      "489  400.0  429.0  437.0  441.0  444.0  447.0  450.0  454.0  463.0  476.0   \n",
      "490  396.0  430.0  435.0  440.0  443.0  448.0  451.0  456.0  460.0  468.0   \n",
      "491  404.0  426.0  434.0  441.0  446.0  450.0  452.0  457.0  462.0  478.0   \n",
      "492  409.0  434.0  439.0  443.0  446.0  450.0  455.0  458.0  464.0  476.0   \n",
      "493  413.0  434.0  439.0  443.0  447.0  451.0  454.0  458.0  467.0  477.0   \n",
      "494  412.0  438.0  444.0  447.0  450.0  454.0  458.0  464.0  468.0  478.0   \n",
      "495  375.0  437.0  442.0  446.0  450.0  454.0  458.0  462.0  468.0  481.0   \n",
      "496  411.0  438.0  443.0  449.0  453.0  455.0  460.0  465.0  471.0  482.0   \n",
      "497  423.0  436.0  444.0  450.0  453.0  457.0  460.0  465.0  468.0  481.0   \n",
      "498  427.0  440.0  447.0  451.0  453.0  457.0  462.0  469.0  478.0  496.0   \n",
      "499  428.0  440.0  448.0  452.0  457.0  462.0  466.0  468.0  478.0  495.0   \n",
      "500  415.0  443.0  449.0  454.0  459.0  463.0  466.0  469.0  475.0  484.0   \n",
      "501  425.0  444.0  450.0  454.0  457.0  460.0  464.0  467.0  473.0  483.0   \n",
      "502  432.0  445.0  451.0  455.0  460.0  463.0  468.0  472.0  476.0  484.0   \n",
      "503  410.0  447.0  452.0  457.0  463.0  466.0  468.0  472.0  477.0  496.0   \n",
      "504  435.0  455.0  459.0  462.0  466.0  469.0  473.0  478.0  487.0  495.0   \n",
      "505  423.0  455.0  463.0  467.0  473.0  475.0  479.0  485.0  493.0  498.0   \n",
      "506  373.0  461.0  469.0  472.0  476.0  480.0  485.0  489.0  498.0  510.0   \n",
      "507  286.0  470.0  478.0  481.0  485.0  489.0  494.0  497.0  504.0  512.0   \n",
      "\n",
      "       100%  \n",
      "0      33.0  \n",
      "1      49.0  \n",
      "2      85.0  \n",
      "3      39.0  \n",
      "4      25.0  \n",
      "5     124.0  \n",
      "6     104.0  \n",
      "7      80.0  \n",
      "8      71.0  \n",
      "9      72.0  \n",
      "10    104.0  \n",
      "11    135.0  \n",
      "12     75.0  \n",
      "13    106.0  \n",
      "14    148.0  \n",
      "15    134.0  \n",
      "16     68.0  \n",
      "17    130.0  \n",
      "18   1416.0  \n",
      "19    186.0  \n",
      "20    149.0  \n",
      "21    169.0  \n",
      "22    910.0  \n",
      "23    823.0  \n",
      "24    205.0  \n",
      "25   1428.0  \n",
      "26    317.0  \n",
      "27   1433.0  \n",
      "28   1433.0  \n",
      "29    505.0  \n",
      "..      ...  \n",
      "478   610.0  \n",
      "479   582.0  \n",
      "480   506.0  \n",
      "481   566.0  \n",
      "482   527.0  \n",
      "483   521.0  \n",
      "484   546.0  \n",
      "485   505.0  \n",
      "486   509.0  \n",
      "487   524.0  \n",
      "488   512.0  \n",
      "489   564.0  \n",
      "490   498.0  \n",
      "491   533.0  \n",
      "492   616.0  \n",
      "493   537.0  \n",
      "494   569.0  \n",
      "495   622.0  \n",
      "496   511.0  \n",
      "497   524.0  \n",
      "498   584.0  \n",
      "499   566.0  \n",
      "500   645.0  \n",
      "501   527.0  \n",
      "502   676.0  \n",
      "503   586.0  \n",
      "504   524.0  \n",
      "505   611.0  \n",
      "506   670.0  \n",
      "507   553.0  \n",
      "\n",
      "[508 rows x 11 columns]\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>departure_delay</th>\n",
       "      <th>0%</th>\n",
       "      <th>10%</th>\n",
       "      <th>20%</th>\n",
       "      <th>30%</th>\n",
       "      <th>40%</th>\n",
       "      <th>50%</th>\n",
       "      <th>60%</th>\n",
       "      <th>70%</th>\n",
       "      <th>80%</th>\n",
       "      <th>90%</th>\n",
       "      <th>100%</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-37.0</td>\n",
       "      <td>-66.0</td>\n",
       "      <td>-44.0</td>\n",
       "      <td>-41.0</td>\n",
       "      <td>-35.0</td>\n",
       "      <td>-30.0</td>\n",
       "      <td>-23.0</td>\n",
       "      <td>-17.0</td>\n",
       "      <td>-12.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-36.0</td>\n",
       "      <td>-74.0</td>\n",
       "      <td>-43.0</td>\n",
       "      <td>-39.0</td>\n",
       "      <td>-37.0</td>\n",
       "      <td>-32.0</td>\n",
       "      <td>-25.0</td>\n",
       "      <td>-18.0</td>\n",
       "      <td>-14.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-35.0</td>\n",
       "      <td>-68.0</td>\n",
       "      <td>-45.0</td>\n",
       "      <td>-40.0</td>\n",
       "      <td>-36.0</td>\n",
       "      <td>-28.0</td>\n",
       "      <td>-19.0</td>\n",
       "      <td>-14.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-34.0</td>\n",
       "      <td>-58.0</td>\n",
       "      <td>-44.0</td>\n",
       "      <td>-40.0</td>\n",
       "      <td>-35.0</td>\n",
       "      <td>-30.0</td>\n",
       "      <td>-25.0</td>\n",
       "      <td>-19.0</td>\n",
       "      <td>-14.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-33.0</td>\n",
       "      <td>-59.0</td>\n",
       "      <td>-43.0</td>\n",
       "      <td>-39.0</td>\n",
       "      <td>-36.0</td>\n",
       "      <td>-32.0</td>\n",
       "      <td>-28.0</td>\n",
       "      <td>-20.0</td>\n",
       "      <td>-14.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   departure_delay    0%   10%   20%   30%   40%   50%   60%   70%  80%  90%  \\\n",
       "0            -37.0 -66.0 -44.0 -41.0 -35.0 -30.0 -23.0 -17.0 -12.0 -3.0  6.0   \n",
       "1            -36.0 -74.0 -43.0 -39.0 -37.0 -32.0 -25.0 -18.0 -14.0 -7.0  2.0   \n",
       "2            -35.0 -68.0 -45.0 -40.0 -36.0 -28.0 -19.0 -14.0  -8.0 -4.0  3.0   \n",
       "3            -34.0 -58.0 -44.0 -40.0 -35.0 -30.0 -25.0 -19.0 -14.0 -8.0  2.0   \n",
       "4            -33.0 -59.0 -43.0 -39.0 -36.0 -32.0 -28.0 -20.0 -14.0 -7.0  5.0   \n",
       "\n",
       "   100%  \n",
       "0  33.0  \n",
       "1  49.0  \n",
       "2  85.0  \n",
       "3  39.0  \n",
       "4  25.0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "percentiles = df['arrival_delay_deciles'].apply(pd.Series)\n",
    "print(percentiles)\n",
    "percentiles = percentiles.rename(columns = lambda x : str(x*10) + \"%\")\n",
    "print(percentiles)\n",
    "df = pd.concat([df['departure_delay'], percentiles], axis=1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/envs/py2env/lib/python2.7/site-packages/matplotlib/font_manager.py:1320: UserWarning: findfont: Font family [u'sans-serif'] not found. Falling back to DejaVu Sans\n",
      "  (prop.get_family(), self.defaultFamily[fontext]))\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1865fb8990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "without_extremes = df.drop(['0%','100%'], 1)\n",
    "without_extremes.plot(x='departure_delay', xlim=(-30,50),  ylim=(-50,50));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f18660bb610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "without_extremes.plot(x='departure_delay');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}