Pandas Dataframe.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Step 1. Let's import Pandas into our Jupyter Notebook environment and read in the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "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>Year</th>\n",
       "      <th>WHO region</th>\n",
       "      <th>Country</th>\n",
       "      <th>Beverage Types</th>\n",
       "      <th>Display Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1986</td>\n",
       "      <td>Western Pacific</td>\n",
       "      <td>Viet Nam</td>\n",
       "      <td>Wine</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1986</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>Wine</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1986</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>Beer</td>\n",
       "      <td>4.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1987</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Saint Kitts and Nevis</td>\n",
       "      <td>Beer</td>\n",
       "      <td>1.98</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year       WHO region                Country Beverage Types  Display Value\n",
       "0  1986  Western Pacific               Viet Nam           Wine           0.00\n",
       "1  1986         Americas                Uruguay          Other           0.50\n",
       "2  1985           Africa           Cte d'Ivoire           Wine           1.62\n",
       "3  1986         Americas               Colombia           Beer           4.27\n",
       "4  1987         Americas  Saint Kitts and Nevis           Beer           1.98"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv('data/world_alcohol.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter by values of one or more Columns using Boolean Logic:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Step 2. Now let's zoom into the _conditional dataset_ with:\n",
    "\n",
    "    df['Year']==1985\n",
    "\n",
    "We'll use head(10) to limit output whenever it's too long."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>WHO region</th>\n",
       "      <th>Country</th>\n",
       "      <th>Beverage Types</th>\n",
       "      <th>Display Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>Wine</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Angola</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>0.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1985</td>\n",
       "      <td>Western Pacific</td>\n",
       "      <td>Lao People's Democratic Republic</td>\n",
       "      <td>Beer</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1985</td>\n",
       "      <td>Western Pacific</td>\n",
       "      <td>Viet Nam</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Comoros</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1985</td>\n",
       "      <td>Europe</td>\n",
       "      <td>United Kingdom of Great Britain and Northern I...</td>\n",
       "      <td>Wine</td>\n",
       "      <td>1.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Mauritania</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>1985</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Saint Kitts and Nevis</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>2.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>1985</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Lithuania</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>1985</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Year       WHO region                                            Country  \\\n",
       "2   1985           Africa                                       Cte d'Ivoire   \n",
       "7   1985           Africa                                             Angola   \n",
       "12  1985  Western Pacific                   Lao People's Democratic Republic   \n",
       "14  1985  Western Pacific                                           Viet Nam   \n",
       "24  1985           Africa                                            Comoros   \n",
       "26  1985           Europe  United Kingdom of Great Britain and Northern I...   \n",
       "33  1985           Africa                                         Mauritania   \n",
       "35  1985         Americas                              Saint Kitts and Nevis   \n",
       "44  1985           Europe                                          Lithuania   \n",
       "50  1985           Europe                                        Switzerland   \n",
       "\n",
       "   Beverage Types  Display Value  \n",
       "2            Wine           1.62  \n",
       "7         Spirits           0.39  \n",
       "12           Beer           0.00  \n",
       "14        Spirits           0.05  \n",
       "24          Other            NaN  \n",
       "26           Wine           1.36  \n",
       "33          Other           0.00  \n",
       "35        Spirits           2.24  \n",
       "44          Other            NaN  \n",
       "50          Other           0.30  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Year']==1985].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Step 3. Let's zoom into the _conditional dataset_ with:\n",
    "    \n",
    "    (df['Year']==1985) OR (df['Year']==1986)\n",
    "\n",
    "As there are multiple conditions, we must enclose them in parentheses now, otherwise it will result in an error."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>WHO region</th>\n",
       "      <th>Country</th>\n",
       "      <th>Beverage Types</th>\n",
       "      <th>Display Value</th>\n",
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       "      <th>0</th>\n",
       "      <td>1986</td>\n",
       "      <td>Western Pacific</td>\n",
       "      <td>Viet Nam</td>\n",
       "      <td>Wine</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1986</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>Wine</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1986</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>Beer</td>\n",
       "      <td>4.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Angola</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>0.39</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1986</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Antigua and Barbuda</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>1.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1985</td>\n",
       "      <td>Western Pacific</td>\n",
       "      <td>Lao People's Democratic Republic</td>\n",
       "      <td>Beer</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1985</td>\n",
       "      <td>Western Pacific</td>\n",
       "      <td>Viet Nam</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1986</td>\n",
       "      <td>South-East Asia</td>\n",
       "      <td>Myanmar</td>\n",
       "      <td>Wine</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Comoros</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Year       WHO region                           Country Beverage Types  \\\n",
       "0   1986  Western Pacific                          Viet Nam           Wine   \n",
       "1   1986         Americas                           Uruguay          Other   \n",
       "2   1985           Africa                      Cte d'Ivoire           Wine   \n",
       "3   1986         Americas                          Colombia           Beer   \n",
       "7   1985           Africa                            Angola        Spirits   \n",
       "8   1986         Americas               Antigua and Barbuda        Spirits   \n",
       "12  1985  Western Pacific  Lao People's Democratic Republic           Beer   \n",
       "14  1985  Western Pacific                          Viet Nam        Spirits   \n",
       "20  1986  South-East Asia                           Myanmar           Wine   \n",
       "24  1985           Africa                           Comoros          Other   \n",
       "\n",
       "    Display Value  \n",
       "0            0.00  \n",
       "1            0.50  \n",
       "2            1.62  \n",
       "3            4.27  \n",
       "7            0.39  \n",
       "8            1.55  \n",
       "12           0.00  \n",
       "14           0.05  \n",
       "20           0.00  \n",
       "24            NaN  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['Year']==1985) | (df['Year']==1986)].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Step 4. The _conditional dataset_ with:\n",
    "\n",
    "    (df['Year']==1985) AND (df['WHO region']=='Africa')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "      <th>Year</th>\n",
       "      <th>WHO region</th>\n",
       "      <th>Country</th>\n",
       "      <th>Beverage Types</th>\n",
       "      <th>Display Value</th>\n",
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       "      <th>2</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>Wine</td>\n",
       "      <td>1.62</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Angola</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>0.39</td>\n",
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       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Comoros</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Mauritania</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.00</td>\n",
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       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Mali</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.57</td>\n",
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       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Comoros</td>\n",
       "      <td>Beer</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Cameroon</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Malawi</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Democratic Republic of the Congo</td>\n",
       "      <td>Wine</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Democratic Republic of the Congo</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Year WHO region                           Country Beverage Types  \\\n",
       "2    1985     Africa                      Cte d'Ivoire           Wine   \n",
       "7    1985     Africa                            Angola        Spirits   \n",
       "24   1985     Africa                           Comoros          Other   \n",
       "33   1985     Africa                        Mauritania          Other   \n",
       "71   1985     Africa                              Mali          Other   \n",
       "76   1985     Africa                           Comoros           Beer   \n",
       "77   1985     Africa                          Cameroon        Spirits   \n",
       "80   1985     Africa                            Malawi          Other   \n",
       "85   1985     Africa  Democratic Republic of the Congo           Wine   \n",
       "118  1985     Africa  Democratic Republic of the Congo        Spirits   \n",
       "\n",
       "     Display Value  \n",
       "2             1.62  \n",
       "7             0.39  \n",
       "24             NaN  \n",
       "33            0.00  \n",
       "71            0.57  \n",
       "76            0.02  \n",
       "77            0.01  \n",
       "80            0.84  \n",
       "85            0.01  \n",
       "118           0.01  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['Year']==1985) & (df['WHO region']=='Africa')].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Step 5. The _conditional dataset_ with:\n",
    "\n",
    "    (df['Year']==1985) AND (df['WHO region']=='Africa') AND (df['Country']=='Comoros')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <th>Beverage Types</th>\n",
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       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Comoros</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Comoros</td>\n",
       "      <td>Beer</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>655</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Comoros</td>\n",
       "      <td>Wine</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1858</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Comoros</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Year WHO region  Country Beverage Types  Display Value\n",
       "24    1985     Africa  Comoros          Other            NaN\n",
       "76    1985     Africa  Comoros           Beer           0.02\n",
       "655   1985     Africa  Comoros           Wine           0.05\n",
       "1858  1985     Africa  Comoros        Spirits           0.30"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['Year']==1985) & (df['WHO region']=='Africa') & (df['Country']=='Comoros')]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Step 6. The _conditional dataset_ with:\n",
    "\n",
    "    ((df['Year']==1985) OR (df['Year']==1986)) AND (df['WHO region']=='Africa')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Year</th>\n",
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       "      <th>Beverage Types</th>\n",
       "      <th>Display Value</th>\n",
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       "      <th>2</th>\n",
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       "      <td>Africa</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>Wine</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Angola</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>0.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Comoros</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1986</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Sierra Leone</td>\n",
       "      <td>Other</td>\n",
       "      <td>4.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Mauritania</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>1986</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Togo</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>0.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>1986</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Madagascar</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>1.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Mali</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Comoros</td>\n",
       "      <td>Beer</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Cameroon</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Year WHO region       Country Beverage Types  Display Value\n",
       "2   1985     Africa  Cte d'Ivoire           Wine           1.62\n",
       "7   1985     Africa        Angola        Spirits           0.39\n",
       "24  1985     Africa       Comoros          Other            NaN\n",
       "30  1986     Africa  Sierra Leone          Other           4.48\n",
       "33  1985     Africa    Mauritania          Other           0.00\n",
       "69  1986     Africa          Togo        Spirits           0.42\n",
       "70  1986     Africa    Madagascar        Spirits           1.02\n",
       "71  1985     Africa          Mali          Other           0.57\n",
       "76  1985     Africa       Comoros           Beer           0.02\n",
       "77  1985     Africa      Cameroon        Spirits           0.01"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[((df['Year']==1985) | (df['Year']==1986))  & (df['WHO region']=='Africa')].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Step 7. The _conditional dataset_ with:\n",
    "\n",
    "    ((df['Year']==1985) OR (df['Year']==1986)) AND ((df['WHO region']=='Africa') OR (df['WHO region']=='Europe'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>WHO region</th>\n",
       "      <th>Country</th>\n",
       "      <th>Beverage Types</th>\n",
       "      <th>Display Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>Wine</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Angola</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>0.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Comoros</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1985</td>\n",
       "      <td>Europe</td>\n",
       "      <td>United Kingdom of Great Britain and Northern I...</td>\n",
       "      <td>Wine</td>\n",
       "      <td>1.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1986</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Italy</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1986</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Sierra Leone</td>\n",
       "      <td>Other</td>\n",
       "      <td>4.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Mauritania</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1986</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Russian Federation</td>\n",
       "      <td>Wine</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>1986</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>Beer</td>\n",
       "      <td>3.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1986</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Czech Republic</td>\n",
       "      <td>Beer</td>\n",
       "      <td>6.82</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Year WHO region                                            Country  \\\n",
       "2   1985     Africa                                       Cte d'Ivoire   \n",
       "7   1985     Africa                                             Angola   \n",
       "24  1985     Africa                                            Comoros   \n",
       "26  1985     Europe  United Kingdom of Great Britain and Northern I...   \n",
       "29  1986     Europe                                              Italy   \n",
       "30  1986     Africa                                       Sierra Leone   \n",
       "33  1985     Africa                                         Mauritania   \n",
       "34  1986     Europe                                 Russian Federation   \n",
       "37  1986     Europe                                             Sweden   \n",
       "41  1986     Europe                                     Czech Republic   \n",
       "\n",
       "   Beverage Types  Display Value  \n",
       "2            Wine           1.62  \n",
       "7         Spirits           0.39  \n",
       "24          Other            NaN  \n",
       "26           Wine           1.36  \n",
       "29          Other            NaN  \n",
       "30          Other           4.48  \n",
       "33          Other           0.00  \n",
       "34           Wine           0.80  \n",
       "37           Beer           3.04  \n",
       "41           Beer           6.82  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[((df['Year']==1985) | (df['Year']==1986)) & ((df['WHO region']=='Africa') | (df['WHO region']=='Europe'))].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So the bottom line is that we can obtain any _conditional dataset_ which is equivalent to zooming into our full dataset by specifying qualifying values for one or more columns. As we zoom into our dataset, the conditional dataset become our new working dataset. \n",
    "\n",
    "Now we can access a single column or a list of columns in any order from this conditional dataset just as we would from the full dataset (it would be returned as a Pandas Series for a single column and a Pandas Dataframe for a list of columns).\n",
    "\n",
    "Step 8. Below we access the 'Country' column from the following _conditional dataset_ which we obtained in Step 6:\n",
    "\n",
    "    ((df['Year']==1985) OR (df['Year']==1986)) AND (df['WHO region']=='Africa')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2     Cte d'Ivoire\n",
       "7           Angola\n",
       "24         Comoros\n",
       "30    Sierra Leone\n",
       "33      Mauritania\n",
       "69            Togo\n",
       "70      Madagascar\n",
       "71            Mali\n",
       "76         Comoros\n",
       "77        Cameroon\n",
       "Name: Country, dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[((df['Year']==1985) | (df['Year']==1986))  & (df['WHO region']=='Africa')]['Country'].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Step 9. We can also access a list of two columns, e.g. 'Country' and 'Beverage Types' as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Beverage Types</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>Wine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Angola</td>\n",
       "      <td>Spirits</td>\n",
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       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Comoros</td>\n",
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       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Sierra Leone</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Mauritania</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Togo</td>\n",
       "      <td>Spirits</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>Madagascar</td>\n",
       "      <td>Spirits</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Mali</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>Comoros</td>\n",
       "      <td>Beer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>Cameroon</td>\n",
       "      <td>Spirits</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Country Beverage Types\n",
       "2   Cte d'Ivoire           Wine\n",
       "7         Angola        Spirits\n",
       "24       Comoros          Other\n",
       "30  Sierra Leone          Other\n",
       "33    Mauritania          Other\n",
       "69          Togo        Spirits\n",
       "70    Madagascar        Spirits\n",
       "71          Mali          Other\n",
       "76       Comoros           Beer\n",
       "77      Cameroon        Spirits"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[((df['Year']==1985) | (df['Year']==1986))  & (df['WHO region']=='Africa')][['Country','Beverage Types']].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Step 10. Now we can access one or more rows from the above using loc (to access by label index) or iloc (to access by integer index) as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country           Madagascar\n",
       "Beverage Types       Spirits\n",
       "Name: 70, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[((df['Year']==1985) | (df['Year']==1986))  & (df['WHO region']=='Africa')][['Country','Beverage Types']].loc[70]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country           Madagascar\n",
       "Beverage Types       Spirits\n",
       "Name: 70, dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[((df['Year']==1985) | (df['Year']==1986))  & (df['WHO region']=='Africa')][['Country','Beverage Types']].iloc[6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>Beverage Types</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <th>7</th>\n",
       "      <td>Angola</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Comoros</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Sierra Leone</td>\n",
       "      <td>Other</td>\n",
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       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Mauritania</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Country Beverage Types\n",
       "2   Cte d'Ivoire           Wine\n",
       "7         Angola        Spirits\n",
       "24       Comoros          Other\n",
       "30  Sierra Leone          Other\n",
       "33    Mauritania          Other"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[((df['Year']==1985) | (df['Year']==1986))  & (df['WHO region']=='Africa')][['Country','Beverage Types']].loc[2:33]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\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>Country</th>\n",
       "      <th>Beverage Types</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>Wine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Angola</td>\n",
       "      <td>Spirits</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Comoros</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Sierra Leone</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Mauritania</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Country Beverage Types\n",
       "2   Cte d'Ivoire           Wine\n",
       "7         Angola        Spirits\n",
       "24       Comoros          Other\n",
       "30  Sierra Leone          Other\n",
       "33    Mauritania          Other"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[((df['Year']==1985) | (df['Year']==1986))  & (df['WHO region']=='Africa')][['Country','Beverage Types']].iloc[0:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Step 11. Because Out [10] and Out [11] is a single row, we can also access its individual elements using index [0] and [1]:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Madagascar'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[((df['Year']==1985) | (df['Year']==1986))  & (df['WHO region']=='Africa')][['Country','Beverage Types']].iloc[6][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Spirits'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[((df['Year']==1985) | (df['Year']==1986))  & (df['WHO region']=='Africa')][['Country','Beverage Types']].iloc[6][1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter by one or more Rows:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So far, we have filtered the dataset using 'one or more conditions on Column values' followed by 'a list of column names', and accessed a row or a list of rows in the end. \n",
    "\n",
    "We will now filter 'one or more rows' which will form our _conditional dataset_, and then access a column or list of columns."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Both df.loc and df.iloc have the following format: \n",
    "\n",
    "    df.iloc[row or range_of_rows or list_of_rows , column or range_of_columns or list_of_columns]\n",
    "\n",
    "If we don't put the separating comma, then the input will be considered as the row or range_of_rows or list_of_rows."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Single row:__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Year                   1987\n",
       "WHO region         Americas\n",
       "Country           Guatemala\n",
       "Beverage Types        Other\n",
       "Display Value             0\n",
       "Name: 5, dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Range of rows:__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "    }\n",
       "\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>Year</th>\n",
       "      <th>WHO region</th>\n",
       "      <th>Country</th>\n",
       "      <th>Beverage Types</th>\n",
       "      <th>Display Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1986</td>\n",
       "      <td>Western Pacific</td>\n",
       "      <td>Viet Nam</td>\n",
       "      <td>Wine</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1986</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>Wine</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1986</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>Beer</td>\n",
       "      <td>4.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1987</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Saint Kitts and Nevis</td>\n",
       "      <td>Beer</td>\n",
       "      <td>1.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1987</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year       WHO region                Country Beverage Types  Display Value\n",
       "0  1986  Western Pacific               Viet Nam           Wine           0.00\n",
       "1  1986         Americas                Uruguay          Other           0.50\n",
       "2  1985           Africa           Cte d'Ivoire           Wine           1.62\n",
       "3  1986         Americas               Colombia           Beer           4.27\n",
       "4  1987         Americas  Saint Kitts and Nevis           Beer           1.98\n",
       "5  1987         Americas              Guatemala          Other           0.00"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[0:6]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__List of rows:__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "\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>Year</th>\n",
       "      <th>WHO region</th>\n",
       "      <th>Country</th>\n",
       "      <th>Beverage Types</th>\n",
       "      <th>Display Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1986</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1986</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>Beer</td>\n",
       "      <td>4.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1987</td>\n",
       "      <td>Americas</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year WHO region    Country Beverage Types  Display Value\n",
       "1  1986   Americas    Uruguay          Other           0.50\n",
       "3  1986   Americas   Colombia           Beer           4.27\n",
       "5  1987   Americas  Guatemala          Other           0.00"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[[1,3,5]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Single column:__ \n",
    "\n",
    "We must now use a colon (for all rows) followed by comma and then the column or range_of_columns or list_of_columns, otherwise we'll get an error."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                 Viet Nam\n",
       "1                  Uruguay\n",
       "2             Cte d'Ivoire\n",
       "3                 Colombia\n",
       "4    Saint Kitts and Nevis\n",
       "5                Guatemala\n",
       "6                Mauritius\n",
       "7                   Angola\n",
       "8      Antigua and Barbuda\n",
       "9                  Nigeria\n",
       "Name: Country, dtype: object"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[:,2].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Range of columns:__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "\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>WHO region</th>\n",
       "      <th>Country</th>\n",
       "      <th>Beverage Types</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Western Pacific</td>\n",
       "      <td>Viet Nam</td>\n",
       "      <td>Wine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Americas</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>Wine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Americas</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>Beer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Americas</td>\n",
       "      <td>Saint Kitts and Nevis</td>\n",
       "      <td>Beer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Americas</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Mauritius</td>\n",
       "      <td>Wine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Angola</td>\n",
       "      <td>Spirits</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Americas</td>\n",
       "      <td>Antigua and Barbuda</td>\n",
       "      <td>Spirits</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        WHO region                Country Beverage Types\n",
       "0  Western Pacific               Viet Nam           Wine\n",
       "1         Americas                Uruguay          Other\n",
       "2           Africa           Cte d'Ivoire           Wine\n",
       "3         Americas               Colombia           Beer\n",
       "4         Americas  Saint Kitts and Nevis           Beer\n",
       "5         Americas              Guatemala          Other\n",
       "6           Africa              Mauritius           Wine\n",
       "7           Africa                 Angola        Spirits\n",
       "8         Americas    Antigua and Barbuda        Spirits\n",
       "9           Africa                Nigeria          Other"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[:,1:4].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__List of columns:__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>Year</th>\n",
       "      <th>Country</th>\n",
       "      <th>Display Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1986</td>\n",
       "      <td>Viet Nam</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1986</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1985</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1986</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>4.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1987</td>\n",
       "      <td>Saint Kitts and Nevis</td>\n",
       "      <td>1.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1987</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1987</td>\n",
       "      <td>Mauritius</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1985</td>\n",
       "      <td>Angola</td>\n",
       "      <td>0.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1986</td>\n",
       "      <td>Antigua and Barbuda</td>\n",
       "      <td>1.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1984</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>6.10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year                Country  Display Value\n",
       "0  1986               Viet Nam           0.00\n",
       "1  1986                Uruguay           0.50\n",
       "2  1985           Cte d'Ivoire           1.62\n",
       "3  1986               Colombia           4.27\n",
       "4  1987  Saint Kitts and Nevis           1.98\n",
       "5  1987              Guatemala           0.00\n",
       "6  1987              Mauritius           0.13\n",
       "7  1985                 Angola           0.39\n",
       "8  1986    Antigua and Barbuda           1.55\n",
       "9  1984                Nigeria           6.10"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[:,[0,2,4]].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now let's explore how to access rows or columns in jumps of an integer index."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Starting from the 'Year' column, access every other column:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Country</th>\n",
       "      <th>Display Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1986</td>\n",
       "      <td>Viet Nam</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1986</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1985</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1986</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>4.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1987</td>\n",
       "      <td>Saint Kitts and Nevis</td>\n",
       "      <td>1.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1987</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1987</td>\n",
       "      <td>Mauritius</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1985</td>\n",
       "      <td>Angola</td>\n",
       "      <td>0.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1986</td>\n",
       "      <td>Antigua and Barbuda</td>\n",
       "      <td>1.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1984</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>6.10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year                Country  Display Value\n",
       "0  1986               Viet Nam           0.00\n",
       "1  1986                Uruguay           0.50\n",
       "2  1985           Cte d'Ivoire           1.62\n",
       "3  1986               Colombia           4.27\n",
       "4  1987  Saint Kitts and Nevis           1.98\n",
       "5  1987              Guatemala           0.00\n",
       "6  1987              Mauritius           0.13\n",
       "7  1985                 Angola           0.39\n",
       "8  1986    Antigua and Barbuda           1.55\n",
       "9  1984                Nigeria           6.10"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[:,'Year'::2].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### And the same thing using iloc:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Country</th>\n",
       "      <th>Display Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1986</td>\n",
       "      <td>Viet Nam</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1986</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1985</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1986</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>4.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1987</td>\n",
       "      <td>Saint Kitts and Nevis</td>\n",
       "      <td>1.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1987</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1987</td>\n",
       "      <td>Mauritius</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1985</td>\n",
       "      <td>Angola</td>\n",
       "      <td>0.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1986</td>\n",
       "      <td>Antigua and Barbuda</td>\n",
       "      <td>1.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1984</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>6.10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year                Country  Display Value\n",
       "0  1986               Viet Nam           0.00\n",
       "1  1986                Uruguay           0.50\n",
       "2  1985           Cte d'Ivoire           1.62\n",
       "3  1986               Colombia           4.27\n",
       "4  1987  Saint Kitts and Nevis           1.98\n",
       "5  1987              Guatemala           0.00\n",
       "6  1987              Mauritius           0.13\n",
       "7  1985                 Angola           0.39\n",
       "8  1986    Antigua and Barbuda           1.55\n",
       "9  1984                Nigeria           6.10"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[:,0::2].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Starting from the 3rd row, access every 4th row:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>WHO region</th>\n",
       "      <th>Country</th>\n",
       "      <th>Beverage Types</th>\n",
       "      <th>Display Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1985</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "      <td>Wine</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1987</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Mauritius</td>\n",
       "      <td>Wine</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1987</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Botswana</td>\n",
       "      <td>Wine</td>\n",
       "      <td>0.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1985</td>\n",
       "      <td>Western Pacific</td>\n",
       "      <td>Viet Nam</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1984</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Norway</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1984</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Romania</td>\n",
       "      <td>Spirits</td>\n",
       "      <td>2.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1985</td>\n",
       "      <td>Europe</td>\n",
       "      <td>United Kingdom of Great Britain and Northern I...</td>\n",
       "      <td>Wine</td>\n",
       "      <td>1.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1986</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Sierra Leone</td>\n",
       "      <td>Other</td>\n",
       "      <td>4.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1986</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Russian Federation</td>\n",
       "      <td>Wine</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>1987</td>\n",
       "      <td>Eastern Mediterranean</td>\n",
       "      <td>Qatar</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Year             WHO region  \\\n",
       "2   1985                 Africa   \n",
       "6   1987                 Africa   \n",
       "10  1987                 Africa   \n",
       "14  1985        Western Pacific   \n",
       "18  1984                 Europe   \n",
       "22  1984                 Europe   \n",
       "26  1985                 Europe   \n",
       "30  1986                 Africa   \n",
       "34  1986                 Europe   \n",
       "38  1987  Eastern Mediterranean   \n",
       "\n",
       "                                              Country Beverage Types  \\\n",
       "2                                        Cte d'Ivoire           Wine   \n",
       "6                                           Mauritius           Wine   \n",
       "10                                           Botswana           Wine   \n",
       "14                                           Viet Nam        Spirits   \n",
       "18                                             Norway        Spirits   \n",
       "22                                            Romania        Spirits   \n",
       "26  United Kingdom of Great Britain and Northern I...           Wine   \n",
       "30                                       Sierra Leone          Other   \n",
       "34                                 Russian Federation           Wine   \n",
       "38                                              Qatar          Other   \n",
       "\n",
       "    Display Value  \n",
       "2            1.62  \n",
       "6            0.13  \n",
       "10           0.20  \n",
       "14           0.05  \n",
       "18           1.62  \n",
       "22           2.67  \n",
       "26           1.36  \n",
       "30           4.48  \n",
       "34           0.80  \n",
       "38           0.00  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[2::4].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### After using loc or iloc to filter rows, we can use bracket notation on top of the resulting conditional dataset to retrieve one or more columns."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First select rows 0 to 4 using iloc on the full dataset, then select column \"WHO region\" from the resulting conditional dataset using bracket notation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    Western Pacific\n",
       "1           Americas\n",
       "2             Africa\n",
       "3           Americas\n",
       "4           Americas\n",
       "Name: WHO region, dtype: object"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[0:5]['WHO region']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First select rows 0 to 4 using iloc on the full dataset, then select columns \"WHO region\" and \"Country\" from the resulting conditional dataset using bracket notation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\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>WHO region</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Western Pacific</td>\n",
       "      <td>Viet Nam</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Americas</td>\n",
       "      <td>Uruguay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Americas</td>\n",
       "      <td>Colombia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Americas</td>\n",
       "      <td>Saint Kitts and Nevis</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        WHO region                Country\n",
       "0  Western Pacific               Viet Nam\n",
       "1         Americas                Uruguay\n",
       "2           Africa           Cte d'Ivoire\n",
       "3         Americas               Colombia\n",
       "4         Americas  Saint Kitts and Nevis"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[0:5][['WHO region','Country']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following is the same as above, but first we select columns \"WHO region\" and \"Country\" from the full dataset using bracket notation, then select rows 0 to 4 using iloc on top of the resulting conditional dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>WHO region</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Western Pacific</td>\n",
       "      <td>Viet Nam</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Americas</td>\n",
       "      <td>Uruguay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Cte d'Ivoire</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Americas</td>\n",
       "      <td>Colombia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Americas</td>\n",
       "      <td>Saint Kitts and Nevis</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        WHO region                Country\n",
       "0  Western Pacific               Viet Nam\n",
       "1         Americas                Uruguay\n",
       "2           Africa           Cte d'Ivoire\n",
       "3         Americas               Colombia\n",
       "4         Americas  Saint Kitts and Nevis"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['WHO region','Country']].iloc[0:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's experiment a bit to see how we can access rows or columns using just the bracket notation."
   ]
  }
 ],
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