Untitled.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "# Read a dataset with missing values\n",
    "flights = pd.read_csv(\"https://raw.githubusercontent.com/roberthryniewicz/datasets/master/airline-dataset/flights/flights.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>DayofMonth</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>DepTime</th>\n",
       "      <th>CRSDepTime</th>\n",
       "      <th>ArrTime</th>\n",
       "      <th>CRSArrTime</th>\n",
       "      <th>UniqueCarrier</th>\n",
       "      <th>FlightNum</th>\n",
       "      <th>...</th>\n",
       "      <th>TaxiIn</th>\n",
       "      <th>TaxiOut</th>\n",
       "      <th>Cancelled</th>\n",
       "      <th>CancellationCode</th>\n",
       "      <th>Diverted</th>\n",
       "      <th>CarrierDelay</th>\n",
       "      <th>WeatherDelay</th>\n",
       "      <th>NASDelay</th>\n",
       "      <th>SecurityDelay</th>\n",
       "      <th>LateAircraftDelay</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>1955</td>\n",
       "      <td>2211.0</td>\n",
       "      <td>2225</td>\n",
       "      <td>WN</td>\n",
       "      <td>335</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>754.0</td>\n",
       "      <td>735</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>1000</td>\n",
       "      <td>WN</td>\n",
       "      <td>3231</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>628.0</td>\n",
       "      <td>620</td>\n",
       "      <td>804.0</td>\n",
       "      <td>750</td>\n",
       "      <td>WN</td>\n",
       "      <td>448</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>926.0</td>\n",
       "      <td>930</td>\n",
       "      <td>1054.0</td>\n",
       "      <td>1100</td>\n",
       "      <td>WN</td>\n",
       "      <td>1746</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1829.0</td>\n",
       "      <td>1755</td>\n",
       "      <td>1959.0</td>\n",
       "      <td>1925</td>\n",
       "      <td>WN</td>\n",
       "      <td>3920</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Month  DayofMonth  DayOfWeek  DepTime  CRSDepTime  ArrTime  \\\n",
       "0  2008      1           3          4   2003.0        1955   2211.0   \n",
       "1  2008      1           3          4    754.0         735   1002.0   \n",
       "2  2008      1           3          4    628.0         620    804.0   \n",
       "3  2008      1           3          4    926.0         930   1054.0   \n",
       "4  2008      1           3          4   1829.0        1755   1959.0   \n",
       "\n",
       "   CRSArrTime UniqueCarrier  FlightNum  ... TaxiIn  TaxiOut  Cancelled  \\\n",
       "0        2225            WN        335  ...    4.0      8.0          0   \n",
       "1        1000            WN       3231  ...    5.0     10.0          0   \n",
       "2         750            WN        448  ...    3.0     17.0          0   \n",
       "3        1100            WN       1746  ...    3.0      7.0          0   \n",
       "4        1925            WN       3920  ...    3.0     10.0          0   \n",
       "\n",
       "   CancellationCode  Diverted  CarrierDelay WeatherDelay NASDelay  \\\n",
       "0               NaN         0           NaN          NaN      NaN   \n",
       "1               NaN         0           NaN          NaN      NaN   \n",
       "2               NaN         0           NaN          NaN      NaN   \n",
       "3               NaN         0           NaN          NaN      NaN   \n",
       "4               NaN         0           2.0          0.0      0.0   \n",
       "\n",
       "   SecurityDelay  LateAircraftDelay  \n",
       "0            NaN                NaN  \n",
       "1            NaN                NaN  \n",
       "2            NaN                NaN  \n",
       "3            NaN                NaN  \n",
       "4            0.0               32.0  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select the rows that have at least one missing value\n",
    "flights[flights.isnull().any(axis=1)].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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