2. Subqueries and Joins in SQLite.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ae93a8cb",
   "metadata": {},
   "source": [
    "### Importing required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b1769d6b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sqlite3 as sql"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a4081c3",
   "metadata": {},
   "source": [
    "### Connecting to the Database\n",
    "* Connecting to the SQLite Database can be established using the connect() method, passing the name of the database to be accessed as a parameter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "aea8d7b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "connection = sql.connect('factbook.db')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "66897ecf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<sqlite3.Connection at 0x261d3ff8b70>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "connection"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3cb9054",
   "metadata": {},
   "source": [
    "### Defining a function to read queries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fbdb6b69",
   "metadata": {},
   "outputs": [],
   "source": [
    "def read(query):\n",
    "    return pd.read_sql_query(query, connection)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38ffbaa7",
   "metadata": {},
   "source": [
    "### The Schema Table"
   ]
  },
  {
   "attachments": {
    "table%20model.JPG": {
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    }
   },
   "cell_type": "markdown",
   "id": "2ef1851f",
   "metadata": {},
   "source": [
    "![table%20model.JPG](attachment:table%20model.JPG)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "81aa51f5",
   "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>type</th>\n",
       "      <th>name</th>\n",
       "      <th>tbl_name</th>\n",
       "      <th>rootpage</th>\n",
       "      <th>sql</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>table</td>\n",
       "      <td>facts</td>\n",
       "      <td>facts</td>\n",
       "      <td>2</td>\n",
       "      <td>CREATE TABLE \"facts\" (\"id\" INTEGER PRIMARY KEY...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>table</td>\n",
       "      <td>sqlite_sequence</td>\n",
       "      <td>sqlite_sequence</td>\n",
       "      <td>3</td>\n",
       "      <td>CREATE TABLE sqlite_sequence(name,seq)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>table</td>\n",
       "      <td>cities</td>\n",
       "      <td>cities</td>\n",
       "      <td>4</td>\n",
       "      <td>CREATE TABLE cities (\\n        id integer prim...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    type             name         tbl_name  rootpage  \\\n",
       "0  table            facts            facts         2   \n",
       "1  table  sqlite_sequence  sqlite_sequence         3   \n",
       "2  table           cities           cities         4   \n",
       "\n",
       "                                                 sql  \n",
       "0  CREATE TABLE \"facts\" (\"id\" INTEGER PRIMARY KEY...  \n",
       "1             CREATE TABLE sqlite_sequence(name,seq)  \n",
       "2  CREATE TABLE cities (\\n        id integer prim...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "read(\"\"\"\n",
    "    SELECT * FROM SQLITE_MASTER\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a3d41de4",
   "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>id</th>\n",
       "      <th>code</th>\n",
       "      <th>name</th>\n",
       "      <th>area</th>\n",
       "      <th>area_land</th>\n",
       "      <th>area_water</th>\n",
       "      <th>population</th>\n",
       "      <th>population_growth</th>\n",
       "      <th>birth_rate</th>\n",
       "      <th>death_rate</th>\n",
       "      <th>migration_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>af</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>652230.0</td>\n",
       "      <td>652230.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32564342.0</td>\n",
       "      <td>2.32</td>\n",
       "      <td>38.57</td>\n",
       "      <td>13.89</td>\n",
       "      <td>1.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>al</td>\n",
       "      <td>Albania</td>\n",
       "      <td>28748.0</td>\n",
       "      <td>27398.0</td>\n",
       "      <td>1350.0</td>\n",
       "      <td>3029278.0</td>\n",
       "      <td>0.30</td>\n",
       "      <td>12.92</td>\n",
       "      <td>6.58</td>\n",
       "      <td>3.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>ag</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>2381741.0</td>\n",
       "      <td>2381741.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39542166.0</td>\n",
       "      <td>1.84</td>\n",
       "      <td>23.67</td>\n",
       "      <td>4.31</td>\n",
       "      <td>0.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>an</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>468.0</td>\n",
       "      <td>468.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85580.0</td>\n",
       "      <td>0.12</td>\n",
       "      <td>8.13</td>\n",
       "      <td>6.96</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>ao</td>\n",
       "      <td>Angola</td>\n",
       "      <td>1246700.0</td>\n",
       "      <td>1246700.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19625353.0</td>\n",
       "      <td>2.78</td>\n",
       "      <td>38.78</td>\n",
       "      <td>11.49</td>\n",
       "      <td>0.46</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id code         name       area  area_land  area_water  population  \\\n",
       "0   1   af  Afghanistan   652230.0   652230.0         0.0  32564342.0   \n",
       "1   2   al      Albania    28748.0    27398.0      1350.0   3029278.0   \n",
       "2   3   ag      Algeria  2381741.0  2381741.0         0.0  39542166.0   \n",
       "3   4   an      Andorra      468.0      468.0         0.0     85580.0   \n",
       "4   5   ao       Angola  1246700.0  1246700.0         0.0  19625353.0   \n",
       "\n",
       "   population_growth  birth_rate  death_rate  migration_rate  \n",
       "0               2.32       38.57       13.89            1.51  \n",
       "1               0.30       12.92        6.58            3.30  \n",
       "2               1.84       23.67        4.31            0.92  \n",
       "3               0.12        8.13        6.96            0.00  \n",
       "4               2.78       38.78       11.49            0.46  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "read(\"\"\"\n",
    "    SELECT * FROM facts\n",
    "\"\"\").head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1feef67c",
   "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>id</th>\n",
       "      <th>name</th>\n",
       "      <th>population</th>\n",
       "      <th>capital</th>\n",
       "      <th>facts_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Oranjestad</td>\n",
       "      <td>37000</td>\n",
       "      <td>1</td>\n",
       "      <td>216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Saint John'S</td>\n",
       "      <td>27000</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>942000</td>\n",
       "      <td>1</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Dubai</td>\n",
       "      <td>1978000</td>\n",
       "      <td>0</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Sharjah</td>\n",
       "      <td>983000</td>\n",
       "      <td>0</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id          name  population  capital facts_id\n",
       "0   1    Oranjestad       37000        1      216\n",
       "1   2  Saint John'S       27000        1        6\n",
       "2   3     Abu Dhabi      942000        1      184\n",
       "3   4         Dubai     1978000        0      184\n",
       "4   5       Sharjah      983000        0      184"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "read(\"\"\"\n",
    "    SELECT * FROM cities\n",
    "\"\"\").head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33fe0ea1",
   "metadata": {},
   "source": [
    "### Join Clause\n",
    "* A JOIN clause combines the records from two tables on the basis of common attributes. \n",
    "* The different types of joins are as follows:\n",
    "    * INNER JOIN (OR JOIN) – Gives the records that have common attributes in both tables.\n",
    "    * LEFT JOIN – Gives all records from the left table and only the common records from the right table.\n",
    "    * RIGHT JOIN – Gives all records from the right table and only the common records from the left table.\n",
    "    * FULL OUTER JOIN – Gives all records when there is a common attribute in either the left or the right table.\n",
    "    * CROSS JOIN – Gives records of one table with all other records of another table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7d006a21",
   "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>id</th>\n",
       "      <th>facts_id</th>\n",
       "      <th>Country</th>\n",
       "      <th>Country</th>\n",
       "      <th>Country_pop</th>\n",
       "      <th>City_pop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>216</td>\n",
       "      <td>216</td>\n",
       "      <td>Aruba</td>\n",
       "      <td>Oranjestad</td>\n",
       "      <td>112162</td>\n",
       "      <td>37000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>Antigua and Barbuda</td>\n",
       "      <td>Saint John'S</td>\n",
       "      <td>92436</td>\n",
       "      <td>27000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>184</td>\n",
       "      <td>184</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>5779760</td>\n",
       "      <td>942000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>184</td>\n",
       "      <td>184</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>Dubai</td>\n",
       "      <td>5779760</td>\n",
       "      <td>1978000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>184</td>\n",
       "      <td>184</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>Sharjah</td>\n",
       "      <td>5779760</td>\n",
       "      <td>983000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>392</th>\n",
       "      <td>167</td>\n",
       "      <td>167</td>\n",
       "      <td>Swaziland</td>\n",
       "      <td>Mbabane</td>\n",
       "      <td>1435613</td>\n",
       "      <td>66000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>393</th>\n",
       "      <td>193</td>\n",
       "      <td>193</td>\n",
       "      <td>Yemen</td>\n",
       "      <td>Sanaa</td>\n",
       "      <td>26737317</td>\n",
       "      <td>2419000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394</th>\n",
       "      <td>193</td>\n",
       "      <td>193</td>\n",
       "      <td>Yemen</td>\n",
       "      <td>Aden</td>\n",
       "      <td>26737317</td>\n",
       "      <td>784000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>395</th>\n",
       "      <td>194</td>\n",
       "      <td>194</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>Lusaka</td>\n",
       "      <td>15066266</td>\n",
       "      <td>1802000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>195</td>\n",
       "      <td>195</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>Harare</td>\n",
       "      <td>14229541</td>\n",
       "      <td>1542000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>397 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id facts_id               Country       Country  Country_pop  City_pop\n",
       "0    216      216                 Aruba    Oranjestad       112162     37000\n",
       "1      6        6   Antigua and Barbuda  Saint John'S        92436     27000\n",
       "2    184      184  United Arab Emirates     Abu Dhabi      5779760    942000\n",
       "3    184      184  United Arab Emirates         Dubai      5779760   1978000\n",
       "4    184      184  United Arab Emirates       Sharjah      5779760    983000\n",
       "..   ...      ...                   ...           ...          ...       ...\n",
       "392  167      167             Swaziland       Mbabane      1435613     66000\n",
       "393  193      193                 Yemen         Sanaa     26737317   2419000\n",
       "394  193      193                 Yemen          Aden     26737317    784000\n",
       "395  194      194                Zambia        Lusaka     15066266   1802000\n",
       "396  195      195              Zimbabwe        Harare     14229541   1542000\n",
       "\n",
       "[397 rows x 6 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "read(\"\"\"\n",
    "    SELECT \n",
    "    \n",
    "    facts.id,\n",
    "    cities.facts_id,\n",
    "    \n",
    "    facts.name AS Country, \n",
    "    cities.name AS Country,\n",
    "    \n",
    "    facts.population AS Country_pop,\n",
    "    cities.population AS City_pop\n",
    "    \n",
    "    FROM facts\n",
    "    \n",
    "    INNER JOIN cities\n",
    "    ON facts.id == cities.facts_id\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "67cabe01",
   "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>Country</th>\n",
       "      <th>City</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Kabul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>Tirana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>Algiers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>Oran</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>Andorra La Vella</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443</th>\n",
       "      <td>Atlantic Ocean</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>Indian Ocean</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>Pacific Ocean</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>Southern Ocean</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>World</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>448 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Country              City\n",
       "0       Afghanistan             Kabul\n",
       "1           Albania            Tirana\n",
       "2           Algeria           Algiers\n",
       "3           Algeria              Oran\n",
       "4           Andorra  Andorra La Vella\n",
       "..              ...               ...\n",
       "443  Atlantic Ocean              None\n",
       "444    Indian Ocean              None\n",
       "445   Pacific Ocean              None\n",
       "446  Southern Ocean              None\n",
       "447           World              None\n",
       "\n",
       "[448 rows x 2 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "read( \"\"\"\n",
    "    SELECT \n",
    "    \n",
    "    facts.name AS Country, cities.name AS City\n",
    "    \n",
    "    FROM facts\n",
    "    \n",
    "    LEFT JOIN cities\n",
    "    ON\n",
    "    facts.id == cities.facts_id\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cfed6e38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\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>Country</th>\n",
       "      <th>City</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Kosovo</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Monaco</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Nauru</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>San Marino</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Singapore</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Holy See (Vatican City)</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Taiwan</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>European Union</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Ashmore and Cartier Islands</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Christmas Island</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Cocos (Keeling) Islands</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Coral Sea Islands</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Heard Island and McDonald Islands</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Norfolk Island</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Hong Kong</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Macau</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Clipperton Island</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>French Southern and Antarctic Lands</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Saint Barthelemy</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Saint Martin</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Curacao</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Sint Maarten</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Cook Islands</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Niue</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Tokelau</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Bouvet Island</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Jan Mayen</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Svalbard</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Akrotiri</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>British Indian Ocean Territory</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Dhekelia</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Gibraltar</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Guernsey</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Jersey</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Montserrat</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Pitcairn Islands</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>South Georgia and South Sandwich Islands</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Navassa Island</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Wake Island</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>United States Pacific Island Wildlife Refuges</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Antarctica</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Gaza Strip</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Paracel Islands</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Spratly Islands</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>West Bank</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Arctic Ocean</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Atlantic Ocean</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Indian Ocean</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Pacific Ocean</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Southern Ocean</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>World</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Country  City\n",
       "0                                          Kosovo  None\n",
       "1                                          Monaco  None\n",
       "2                                           Nauru  None\n",
       "3                                      San Marino  None\n",
       "4                                       Singapore  None\n",
       "5                         Holy See (Vatican City)  None\n",
       "6                                          Taiwan  None\n",
       "7                                  European Union  None\n",
       "8                     Ashmore and Cartier Islands  None\n",
       "9                                Christmas Island  None\n",
       "10                        Cocos (Keeling) Islands  None\n",
       "11                              Coral Sea Islands  None\n",
       "12              Heard Island and McDonald Islands  None\n",
       "13                                 Norfolk Island  None\n",
       "14                                      Hong Kong  None\n",
       "15                                          Macau  None\n",
       "16                              Clipperton Island  None\n",
       "17            French Southern and Antarctic Lands  None\n",
       "18                               Saint Barthelemy  None\n",
       "19                                   Saint Martin  None\n",
       "20                                        Curacao  None\n",
       "21                                   Sint Maarten  None\n",
       "22                                   Cook Islands  None\n",
       "23                                           Niue  None\n",
       "24                                        Tokelau  None\n",
       "25                                  Bouvet Island  None\n",
       "26                                      Jan Mayen  None\n",
       "27                                       Svalbard  None\n",
       "28                                       Akrotiri  None\n",
       "29                 British Indian Ocean Territory  None\n",
       "30                                       Dhekelia  None\n",
       "31                                      Gibraltar  None\n",
       "32                                       Guernsey  None\n",
       "33                                         Jersey  None\n",
       "34                                     Montserrat  None\n",
       "35                               Pitcairn Islands  None\n",
       "36       South Georgia and South Sandwich Islands  None\n",
       "37                                 Navassa Island  None\n",
       "38                                    Wake Island  None\n",
       "39  United States Pacific Island Wildlife Refuges  None\n",
       "40                                     Antarctica  None\n",
       "41                                     Gaza Strip  None\n",
       "42                                Paracel Islands  None\n",
       "43                                Spratly Islands  None\n",
       "44                                      West Bank  None\n",
       "45                                   Arctic Ocean  None\n",
       "46                                 Atlantic Ocean  None\n",
       "47                                   Indian Ocean  None\n",
       "48                                  Pacific Ocean  None\n",
       "49                                 Southern Ocean  None\n",
       "50                                          World  None"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "read(\"\"\"\n",
    "    SELECT \n",
    "    facts.name AS Country, cities.name AS City\n",
    "    FROM facts\n",
    "    \n",
    "    LEFT JOIN cities\n",
    "    ON\n",
    "    facts.id == cities.facts_id\n",
    "    WHERE City is null\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8f7a2599",
   "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>Country</th>\n",
       "      <th>Country_pop</th>\n",
       "      <th>City_pop</th>\n",
       "      <th>Pop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>32564342</td>\n",
       "      <td>3097000</td>\n",
       "      <td>0.095104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>3029278</td>\n",
       "      <td>419000</td>\n",
       "      <td>0.138317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>39542166</td>\n",
       "      <td>2916000</td>\n",
       "      <td>0.073744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>54343</td>\n",
       "      <td>64000</td>\n",
       "      <td>1.177705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>85580</td>\n",
       "      <td>23000</td>\n",
       "      <td>0.268754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>Wallis and Futuna</td>\n",
       "      <td>15613</td>\n",
       "      <td>1000</td>\n",
       "      <td>0.064049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>Western Sahara</td>\n",
       "      <td>570866</td>\n",
       "      <td>237000</td>\n",
       "      <td>0.415159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>26737317</td>\n",
       "      <td>2419000</td>\n",
       "      <td>0.090473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>15066266</td>\n",
       "      <td>1802000</td>\n",
       "      <td>0.119605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>14229541</td>\n",
       "      <td>1542000</td>\n",
       "      <td>0.108366</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>210 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Country  Country_pop  City_pop       Pop\n",
       "0          Afghanistan     32564342   3097000  0.095104\n",
       "1              Albania      3029278    419000  0.138317\n",
       "2              Algeria     39542166   2916000  0.073744\n",
       "3       American Samoa        54343     64000  1.177705\n",
       "4              Andorra        85580     23000  0.268754\n",
       "..                 ...          ...       ...       ...\n",
       "205  Wallis and Futuna        15613      1000  0.064049\n",
       "206     Western Sahara       570866    237000  0.415159\n",
       "207              Yemen     26737317   2419000  0.090473\n",
       "208             Zambia     15066266   1802000  0.119605\n",
       "209           Zimbabwe     14229541   1542000  0.108366\n",
       "\n",
       "[210 rows x 4 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "read(\"\"\"\n",
    "    SELECT \n",
    "    facts.name AS Country, \n",
    "    facts.population AS Country_pop, \n",
    "    cities.population AS City_pop,\n",
    "    cities.population/CAST(facts.population as float) AS Pop\n",
    "    FROM facts\n",
    "    INNER JOIN cities\n",
    "    ON\n",
    "    facts.id == cities.facts_id\n",
    "    GROUP BY facts.name \n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6bdd84c0",
   "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>facts_id</th>\n",
       "      <th>urban_pop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>3097000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>172000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>100</td>\n",
       "      <td>1127000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>101</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>102</td>\n",
       "      <td>546000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>95</td>\n",
       "      <td>810000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>96</td>\n",
       "      <td>701000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>97</td>\n",
       "      <td>2022000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>98</td>\n",
       "      <td>239000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>99</td>\n",
       "      <td>750000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>210 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    facts_id  urban_pop\n",
       "0          1    3097000\n",
       "1         10     172000\n",
       "2        100    1127000\n",
       "3        101       5000\n",
       "4        102     546000\n",
       "..       ...        ...\n",
       "205       95     810000\n",
       "206       96     701000\n",
       "207       97    2022000\n",
       "208       98     239000\n",
       "209       99     750000\n",
       "\n",
       "[210 rows x 2 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "read( \"\"\"\n",
    "    SELECT \n",
    "    facts_id,\n",
    "    sum(population) AS urban_pop \n",
    "    FROM cities\n",
    "    GROUP BY facts_id\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ab5c530",
   "metadata": {},
   "source": [
    "### Subquery\n",
    "* A subquery is a SQL query nested inside a larger query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "98842822",
   "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>Country</th>\n",
       "      <th>Country_pop</th>\n",
       "      <th>urban_pop</th>\n",
       "      <th>Pepcentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>32564342</td>\n",
       "      <td>3097000</td>\n",
       "      <td>0.095104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>3029278</td>\n",
       "      <td>419000</td>\n",
       "      <td>0.138317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>39542166</td>\n",
       "      <td>3699000</td>\n",
       "      <td>0.093546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>54343</td>\n",
       "      <td>64000</td>\n",
       "      <td>1.177705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>85580</td>\n",
       "      <td>23000</td>\n",
       "      <td>0.268754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>Wallis and Futuna</td>\n",
       "      <td>15613</td>\n",
       "      <td>1000</td>\n",
       "      <td>0.064049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>Western Sahara</td>\n",
       "      <td>570866</td>\n",
       "      <td>237000</td>\n",
       "      <td>0.415159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>26737317</td>\n",
       "      <td>3203000</td>\n",
       "      <td>0.119795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>15066266</td>\n",
       "      <td>1802000</td>\n",
       "      <td>0.119605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>14229541</td>\n",
       "      <td>1542000</td>\n",
       "      <td>0.108366</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>210 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Country  Country_pop  urban_pop  Pepcentage\n",
       "0          Afghanistan     32564342    3097000    0.095104\n",
       "1              Albania      3029278     419000    0.138317\n",
       "2              Algeria     39542166    3699000    0.093546\n",
       "3       American Samoa        54343      64000    1.177705\n",
       "4              Andorra        85580      23000    0.268754\n",
       "..                 ...          ...        ...         ...\n",
       "205  Wallis and Futuna        15613       1000    0.064049\n",
       "206     Western Sahara       570866     237000    0.415159\n",
       "207              Yemen     26737317    3203000    0.119795\n",
       "208             Zambia     15066266    1802000    0.119605\n",
       "209           Zimbabwe     14229541    1542000    0.108366\n",
       "\n",
       "[210 rows x 4 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "read(\"\"\"\n",
    "    SELECT \n",
    "    f.name Country, f.population Country_pop ,\n",
    "    a.urban_pop, a.urban_pop/CAST(f.population as float) Pepcentage\n",
    "    from facts as f\n",
    "    inner join (SELECT facts_id,  sum(population) urban_pop from cities group by facts_id) as a\n",
    "    on f.id == a.facts_id\n",
    "    Group by f.name \n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32fb9c8e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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