DataCleaningAssignment.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2.Problem Statement:\n",
    "\n",
    "It happens all the time: someone gives you data containing malformed strings, Python, lists and missing data. How do you tidy it up so you can get on with the analysis? \n",
    "Take this monstrosity as the DataFrame to use in the following puzzles:\n",
    "df = pd.DataFrame({\n",
    "'From_To': ['LoNDon_paris', 'MAdrid_miLAN', 'londON_StockhOlm','Budapest_PaRis', 'Brussels_londOn'],\n",
    "'FlightNumber': [10045, np.nan, 10065, np.nan, 10085],\n",
    "'RecentDelays': [[23, 47], [], [24, 43, 87], [13], [67, 32]],\n",
    "'Airline': ['KLM(!)', '<Air France>(12)','(Britid=sh Airways.  )','12. Air France', '\"Swiss Air\"']\n",
    "})\n",
    "Some values in the the FlightNumber column are missing. \n",
    "These numbers are meant to increase by 10 with each row so 10055 and 10075 need to be put in place. \n",
    "Fill in these missing numbers and make the column an integer column (instead of a float column)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame({\n",
    "    'From_To': ['LoNDon_paris', 'MAdrid_miLAN', 'londON_StockhOlm',\n",
    "\n",
    "'Budapest_PaRis', 'Brussels_londOn'],\n",
    "\n",
    "'FlightNumber': [10045, np.nan, 10065, np.nan, 10085],\n",
    "\n",
    "'RecentDelays': [[23, 47], [], [24, 43, 87], [13], [67, 32]],\n",
    "\n",
    "'Airline': ['KLM(!)', ' (12)', '(British Airways. )',\n",
    "\n",
    "'12. Air France', '\"Swiss Air\"']})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>From_To</th>\n",
       "      <th>FlightNumber</th>\n",
       "      <th>RecentDelays</th>\n",
       "      <th>Airline</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LoNDon_paris</td>\n",
       "      <td>10045.0</td>\n",
       "      <td>[23, 47]</td>\n",
       "      <td>KLM(!)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MAdrid_miLAN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[]</td>\n",
       "      <td>(12)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>londON_StockhOlm</td>\n",
       "      <td>10065.0</td>\n",
       "      <td>[24, 43, 87]</td>\n",
       "      <td>(British Airways. )</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Budapest_PaRis</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[13]</td>\n",
       "      <td>12. Air France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Brussels_londOn</td>\n",
       "      <td>10085.0</td>\n",
       "      <td>[67, 32]</td>\n",
       "      <td>\"Swiss Air\"</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            From_To  FlightNumber  RecentDelays              Airline\n",
       "0      LoNDon_paris       10045.0      [23, 47]               KLM(!)\n",
       "1      MAdrid_miLAN           NaN            []                 (12)\n",
       "2  londON_StockhOlm       10065.0  [24, 43, 87]  (British Airways. )\n",
       "3    Budapest_PaRis           NaN          [13]       12. Air France\n",
       "4   Brussels_londOn       10085.0      [67, 32]          \"Swiss Air\""
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5 entries, 0 to 4\n",
      "Data columns (total 4 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   From_To       5 non-null      object \n",
      " 1   FlightNumber  3 non-null      float64\n",
      " 2   RecentDelays  5 non-null      object \n",
      " 3   Airline       5 non-null      object \n",
      "dtypes: float64(1), object(3)\n",
      "memory usage: 288.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "df.isna().values\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>From_To</th>\n",
       "      <th>FlightNumber</th>\n",
       "      <th>RecentDelays</th>\n",
       "      <th>Airline</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LoNDon_paris</td>\n",
       "      <td>10045.0</td>\n",
       "      <td>[23, 47]</td>\n",
       "      <td>KLM(!)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MAdrid_miLAN</td>\n",
       "      <td>10055.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>(12)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>londON_StockhOlm</td>\n",
       "      <td>10065.0</td>\n",
       "      <td>[24, 43, 87]</td>\n",
       "      <td>(British Airways. )</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Budapest_PaRis</td>\n",
       "      <td>10075.0</td>\n",
       "      <td>[13]</td>\n",
       "      <td>12. Air France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Brussels_londOn</td>\n",
       "      <td>10085.0</td>\n",
       "      <td>[67, 32]</td>\n",
       "      <td>\"Swiss Air\"</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            From_To  FlightNumber  RecentDelays              Airline\n",
       "0      LoNDon_paris       10045.0      [23, 47]               KLM(!)\n",
       "1      MAdrid_miLAN       10055.0            []                 (12)\n",
       "2  londON_StockhOlm       10065.0  [24, 43, 87]  (British Airways. )\n",
       "3    Budapest_PaRis       10075.0          [13]       12. Air France\n",
       "4   Brussels_londOn       10085.0      [67, 32]          \"Swiss Air\""
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fight_number = df['FlightNumber']\n",
    "df.iloc[1,1] = fight_number[0]+10\n",
    "df.iloc[3,1] = fight_number[2]+10\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>From_To</th>\n",
       "      <th>FlightNumber</th>\n",
       "      <th>RecentDelays</th>\n",
       "      <th>Airline</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LoNDon_paris</td>\n",
       "      <td>10045</td>\n",
       "      <td>[23, 47]</td>\n",
       "      <td>KLM(!)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MAdrid_miLAN</td>\n",
       "      <td>10055</td>\n",
       "      <td>[]</td>\n",
       "      <td>(12)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>londON_StockhOlm</td>\n",
       "      <td>10065</td>\n",
       "      <td>[24, 43, 87]</td>\n",
       "      <td>(British Airways. )</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Budapest_PaRis</td>\n",
       "      <td>10075</td>\n",
       "      <td>[13]</td>\n",
       "      <td>12. Air France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Brussels_londOn</td>\n",
       "      <td>10085</td>\n",
       "      <td>[67, 32]</td>\n",
       "      <td>\"Swiss Air\"</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            From_To  FlightNumber  RecentDelays              Airline\n",
       "0      LoNDon_paris         10045      [23, 47]               KLM(!)\n",
       "1      MAdrid_miLAN         10055            []                 (12)\n",
       "2  londON_StockhOlm         10065  [24, 43, 87]  (British Airways. )\n",
       "3    Budapest_PaRis         10075          [13]       12. Air France\n",
       "4   Brussels_londOn         10085      [67, 32]          \"Swiss Air\""
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['FlightNumber'] = df['FlightNumber'].astype(int)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The FromTo column would be better as two separate columns! Split each string on the underscore delimiter to give a new temporary DataFrame with the correct values. Assign the correct column names to this temporary DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>From_To</th>\n",
       "      <th>FlightNumber</th>\n",
       "      <th>RecentDelays</th>\n",
       "      <th>Airline</th>\n",
       "      <th>From</th>\n",
       "      <th>To</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LoNDon_paris</td>\n",
       "      <td>10045</td>\n",
       "      <td>[23, 47]</td>\n",
       "      <td>KLM(!)</td>\n",
       "      <td>LoNDon</td>\n",
       "      <td>paris</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MAdrid_miLAN</td>\n",
       "      <td>10055</td>\n",
       "      <td>[]</td>\n",
       "      <td>(12)</td>\n",
       "      <td>MAdrid</td>\n",
       "      <td>miLAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>londON_StockhOlm</td>\n",
       "      <td>10065</td>\n",
       "      <td>[24, 43, 87]</td>\n",
       "      <td>(British Airways. )</td>\n",
       "      <td>londON</td>\n",
       "      <td>StockhOlm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Budapest_PaRis</td>\n",
       "      <td>10075</td>\n",
       "      <td>[13]</td>\n",
       "      <td>12. Air France</td>\n",
       "      <td>Budapest</td>\n",
       "      <td>PaRis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Brussels_londOn</td>\n",
       "      <td>10085</td>\n",
       "      <td>[67, 32]</td>\n",
       "      <td>\"Swiss Air\"</td>\n",
       "      <td>Brussels</td>\n",
       "      <td>londOn</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            From_To  FlightNumber  RecentDelays              Airline  \\\n",
       "0      LoNDon_paris         10045      [23, 47]               KLM(!)   \n",
       "1      MAdrid_miLAN         10055            []                 (12)   \n",
       "2  londON_StockhOlm         10065  [24, 43, 87]  (British Airways. )   \n",
       "3    Budapest_PaRis         10075          [13]       12. Air France   \n",
       "4   Brussels_londOn         10085      [67, 32]          \"Swiss Air\"   \n",
       "\n",
       "       From         To  \n",
       "0    LoNDon      paris  \n",
       "1    MAdrid      miLAN  \n",
       "2    londON  StockhOlm  \n",
       "3  Budapest      PaRis  \n",
       "4  Brussels     londOn  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy = df.copy()\n",
    "from_to = df_copy['From_To'].str.split(\"_\",n = 1, expand = True)\n",
    "df_copy['From'] = from_to[0]\n",
    "df_copy['To'] = from_to[1]\n",
    "df_copy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Notice how the capitalisation of the city names is all mixed up in this temporary DataFrame. Standardise the strings so that only the first letter is uppercase (e.g. \"londON\" should become \"London\".)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>From_To</th>\n",
       "      <th>FlightNumber</th>\n",
       "      <th>RecentDelays</th>\n",
       "      <th>Airline</th>\n",
       "      <th>From</th>\n",
       "      <th>To</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LoNDon_paris</td>\n",
       "      <td>10045</td>\n",
       "      <td>[23, 47]</td>\n",
       "      <td>KLM(!)</td>\n",
       "      <td>London</td>\n",
       "      <td>Paris</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MAdrid_miLAN</td>\n",
       "      <td>10055</td>\n",
       "      <td>[]</td>\n",
       "      <td>(12)</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Milan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>londON_StockhOlm</td>\n",
       "      <td>10065</td>\n",
       "      <td>[24, 43, 87]</td>\n",
       "      <td>(British Airways. )</td>\n",
       "      <td>London</td>\n",
       "      <td>Stockholm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Budapest_PaRis</td>\n",
       "      <td>10075</td>\n",
       "      <td>[13]</td>\n",
       "      <td>12. Air France</td>\n",
       "      <td>Budapest</td>\n",
       "      <td>Paris</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Brussels_londOn</td>\n",
       "      <td>10085</td>\n",
       "      <td>[67, 32]</td>\n",
       "      <td>\"Swiss Air\"</td>\n",
       "      <td>Brussels</td>\n",
       "      <td>London</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            From_To  FlightNumber  RecentDelays              Airline  \\\n",
       "0      LoNDon_paris         10045      [23, 47]               KLM(!)   \n",
       "1      MAdrid_miLAN         10055            []                 (12)   \n",
       "2  londON_StockhOlm         10065  [24, 43, 87]  (British Airways. )   \n",
       "3    Budapest_PaRis         10075          [13]       12. Air France   \n",
       "4   Brussels_londOn         10085      [67, 32]          \"Swiss Air\"   \n",
       "\n",
       "       From         To  \n",
       "0    London      Paris  \n",
       "1    Madrid      Milan  \n",
       "2    London  Stockholm  \n",
       "3  Budapest      Paris  \n",
       "4  Brussels     London  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_copy['From'] = df_copy['From'].str.capitalize()\n",
    "df_copy['To'] = df_copy['To'].str.capitalize()\n",
    "df_copy\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Delete the From_To column from df and attach the temporary DataFrame from the previous questions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FlightNumber</th>\n",
       "      <th>RecentDelays</th>\n",
       "      <th>Airline</th>\n",
       "      <th>From</th>\n",
       "      <th>To</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10045</td>\n",
       "      <td>[23, 47]</td>\n",
       "      <td>KLM(!)</td>\n",
       "      <td>London</td>\n",
       "      <td>Paris</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10055</td>\n",
       "      <td>[]</td>\n",
       "      <td>(12)</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Milan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10065</td>\n",
       "      <td>[24, 43, 87]</td>\n",
       "      <td>(British Airways. )</td>\n",
       "      <td>London</td>\n",
       "      <td>Stockholm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10075</td>\n",
       "      <td>[13]</td>\n",
       "      <td>12. Air France</td>\n",
       "      <td>Budapest</td>\n",
       "      <td>Paris</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10085</td>\n",
       "      <td>[67, 32]</td>\n",
       "      <td>\"Swiss Air\"</td>\n",
       "      <td>Brussels</td>\n",
       "      <td>London</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   FlightNumber  RecentDelays              Airline      From         To\n",
       "0         10045      [23, 47]               KLM(!)    London      Paris\n",
       "1         10055            []                 (12)    Madrid      Milan\n",
       "2         10065  [24, 43, 87]  (British Airways. )    London  Stockholm\n",
       "3         10075          [13]       12. Air France  Budapest      Paris\n",
       "4         10085      [67, 32]          \"Swiss Air\"  Brussels     London"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "del df_copy['From_To']\n",
    "df = df_copy\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5. In the RecentDelays column, the values have been entered into the DataFrame as a list. We would like each first value in its own column, each\n",
    "second value in its own column, and so on. If there isn't an Nth value, the value should be NaN. Expand the Series of lists into a DataFrame named delays, rename the columns delay_1, delay_2, etc. and replace the unwanted RecentDelays column in df with delays."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>delays1</th>\n",
       "      <th>delays2</th>\n",
       "      <th>delays3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>23.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>87.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>67.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   delays1  delays2  delays3\n",
       "0     23.0     47.0      NaN\n",
       "1      NaN      NaN      NaN\n",
       "2     24.0     43.0     87.0\n",
       "3     13.0      NaN      NaN\n",
       "4     67.0     32.0      NaN"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "delays = pd.DataFrame(df['RecentDelays'])\n",
    "pd.DataFrame(delays.RecentDelays.values.tolist())\n",
    "df2 = pd.DataFrame(delays.RecentDelays.values.tolist(),columns= ['delays1','delays2','delays3'])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>FlightNumber</th>\n",
       "      <th>RecentDelays</th>\n",
       "      <th>Airline</th>\n",
       "      <th>From</th>\n",
       "      <th>To</th>\n",
       "      <th>delays2</th>\n",
       "      <th>delays3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10045</td>\n",
       "      <td>23.0</td>\n",
       "      <td>KLM(!)</td>\n",
       "      <td>London</td>\n",
       "      <td>Paris</td>\n",
       "      <td>47.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10055</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(12)</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>Milan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10065</td>\n",
       "      <td>24.0</td>\n",
       "      <td>(British Airways. )</td>\n",
       "      <td>London</td>\n",
       "      <td>Stockholm</td>\n",
       "      <td>43.0</td>\n",
       "      <td>87.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10075</td>\n",
       "      <td>13.0</td>\n",
       "      <td>12. Air France</td>\n",
       "      <td>Budapest</td>\n",
       "      <td>Paris</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10085</td>\n",
       "      <td>67.0</td>\n",
       "      <td>\"Swiss Air\"</td>\n",
       "      <td>Brussels</td>\n",
       "      <td>London</td>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   FlightNumber  RecentDelays              Airline      From         To  \\\n",
       "0         10045          23.0               KLM(!)    London      Paris   \n",
       "1         10055           NaN                 (12)    Madrid      Milan   \n",
       "2         10065          24.0  (British Airways. )    London  Stockholm   \n",
       "3         10075          13.0       12. Air France  Budapest      Paris   \n",
       "4         10085          67.0          \"Swiss Air\"  Brussels     London   \n",
       "\n",
       "   delays2  delays3  \n",
       "0     47.0      NaN  \n",
       "1      NaN      NaN  \n",
       "2     43.0     87.0  \n",
       "3      NaN      NaN  \n",
       "4     32.0      NaN  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['RecentDelays'] = df2\n",
    "\n",
    "df['delays2']=df2['delays2']\n",
    "df['delays3']= df2['delays3']\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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