4) SQLmagic_SQlite.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style=\"text-align:center\">\n",
    "    <a href=\"https://skills.network/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkDB0201ENSkillsNetwork20127838-2022-01-01\" target=\"_blank\">\n",
    "    <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/assets/logos/SN_web_lightmode.png\" width=\"200\" alt=\"Skills Network Logo\"  />\n",
    "    </a>\n",
    "</p>\n",
    "\n",
    "# Accessing Databases with SQL Magic\n",
    "\n",
    "Estimated time needed: **15** minutes\n",
    "\n",
    "## Objectives\n",
    "\n",
    "After completing this lab you will be able to:\n",
    "\n",
    "*   Perform simplified database access using SQL \"magic\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### To communicate with SQL Databases from within a JupyterLab notebook, we can use the SQL \"magic\" provided by the [ipython-sql](https://github.com/catherinedevlin/ipython-sql) extension. \"Magic\" is JupyterLab's term for special commands that start with \"%\". Below, we'll use the *load*\\_*ext* magic to load the ipython-sql extension. In the lab environemnt provided in the course the ipython-sql extension is already installed and so is the ibm_db_sa driver.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext sql"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Here  you will  be creating and connecting to a new SQlite database SQLiteMagic.\n",
    "\n",
    "### The syntax for connecting to magic sql using sqllite is\n",
    "\n",
    "**%sql sqlite://DatabaseName**\n",
    "\n",
    "### where DatabaseName will be your **.db** file\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import csv, sqlite3\n",
    "\n",
    "con = sqlite3.connect(\"SQLiteMagic.db\")\n",
    "cur = con.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The sql extension is already loaded. To reload it, use:\n",
      "  %reload_ext sql\n"
     ]
    }
   ],
   "source": [
    "%load_ext sql"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Connected: @SQLiteMagic.db'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql sqlite:///SQLiteMagic.db"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### For convenience, we can use %%sql (two %'s instead of one) at the top of a cell to indicate we want the entire cell to be treated as SQL. Let's use this to create a table and fill it with some test data for experimenting.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///SQLiteMagic.db\n",
      "(sqlite3.OperationalError) table INTERNATIONAL_STUDENT_TEST_SCORES already exists\n",
      "[SQL: CREATE TABLE INTERNATIONAL_STUDENT_TEST_SCORES (\n",
      "\tcountry VARCHAR(50),\n",
      "\tfirst_name VARCHAR(50),\n",
      "\tlast_name VARCHAR(50),\n",
      "\ttest_score INT\n",
      ");]\n",
      "(Background on this error at: http://sqlalche.me/e/13/e3q8)\n"
     ]
    }
   ],
   "source": [
    "%%sql\n",
    "\n",
    "CREATE TABLE INTERNATIONAL_STUDENT_TEST_SCORES (\n",
    "\tcountry VARCHAR(50),\n",
    "\tfirst_name VARCHAR(50),\n",
    "\tlast_name VARCHAR(50),\n",
    "\ttest_score INT\n",
    ");\n",
    "INSERT INTO INTERNATIONAL_STUDENT_TEST_SCORES (country, first_name, last_name, test_score)\n",
    "VALUES\n",
    "('United States', 'Marshall', 'Bernadot', 54),\n",
    "('Ghana', 'Celinda', 'Malkin', 51),\n",
    "('Ukraine', 'Guillermo', 'Furze', 53),\n",
    "('Greece', 'Aharon', 'Tunnow', 48),\n",
    "('Russia', 'Bail', 'Goodwin', 46),\n",
    "('Poland', 'Cole', 'Winteringham', 49),\n",
    "('Sweden', 'Emlyn', 'Erricker', 55),\n",
    "('Russia', 'Cathee', 'Sivewright', 49),\n",
    "('China', 'Barny', 'Ingerson', 57),\n",
    "('Uganda', 'Sharla', 'Papaccio', 55),\n",
    "('China', 'Stella', 'Youens', 51),\n",
    "('Poland', 'Julio', 'Buesden', 48),\n",
    "('United States', 'Tiffie', 'Cosely', 58),\n",
    "('Poland', 'Auroora', 'Stiffell', 45),\n",
    "('China', 'Clarita', 'Huet', 52),\n",
    "('Poland', 'Shannon', 'Goulden', 45),\n",
    "('Philippines', 'Emylee', 'Privost', 50),\n",
    "('France', 'Madelina', 'Burk', 49),\n",
    "('China', 'Saunderson', 'Root', 58),\n",
    "('Indonesia', 'Bo', 'Waring', 55),\n",
    "('China', 'Hollis', 'Domotor', 45),\n",
    "('Russia', 'Robbie', 'Collip', 46),\n",
    "('Philippines', 'Davon', 'Donisi', 46),\n",
    "('China', 'Cristabel', 'Radeliffe', 48),\n",
    "('China', 'Wallis', 'Bartleet', 58),\n",
    "('Moldova', 'Arleen', 'Stailey', 38),\n",
    "('Ireland', 'Mendel', 'Grumble', 58),\n",
    "('China', 'Sallyann', 'Exley', 51),\n",
    "('Mexico', 'Kain', 'Swaite', 46),\n",
    "('Indonesia', 'Alonso', 'Bulteel', 45),\n",
    "('Armenia', 'Anatol', 'Tankus', 51),\n",
    "('Indonesia', 'Coralyn', 'Dawkins', 48),\n",
    "('China', 'Deanne', 'Edwinson', 45),\n",
    "('China', 'Georgiana', 'Epple', 51),\n",
    "('Portugal', 'Bartlet', 'Breese', 56),\n",
    "('Azerbaijan', 'Idalina', 'Lukash', 50),\n",
    "('France', 'Livvie', 'Flory', 54),\n",
    "('Malaysia', 'Nonie', 'Borit', 48),\n",
    "('Indonesia', 'Clio', 'Mugg', 47),\n",
    "('Brazil', 'Westley', 'Measor', 48),\n",
    "('Philippines', 'Katrinka', 'Sibbert', 51),\n",
    "('Poland', 'Valentia', 'Mounch', 50),\n",
    "('Norway', 'Sheilah', 'Hedditch', 53),\n",
    "('Papua New Guinea', 'Itch', 'Jubb', 50),\n",
    "('Latvia', 'Stesha', 'Garnson', 53),\n",
    "('Canada', 'Cristionna', 'Wadmore', 46),\n",
    "('China', 'Lianna', 'Gatward', 43),\n",
    "('Guatemala', 'Tanney', 'Vials', 48),\n",
    "('France', 'Alma', 'Zavittieri', 44),\n",
    "('China', 'Alvira', 'Tamas', 50),\n",
    "('United States', 'Shanon', 'Peres', 45),\n",
    "('Sweden', 'Maisey', 'Lynas', 53),\n",
    "('Indonesia', 'Kip', 'Hothersall', 46),\n",
    "('China', 'Cash', 'Landis', 48),\n",
    "('Panama', 'Kennith', 'Digance', 45),\n",
    "('China', 'Ulberto', 'Riggeard', 48),\n",
    "('Switzerland', 'Judy', 'Gilligan', 49),\n",
    "('Philippines', 'Tod', 'Trevaskus', 52),\n",
    "('Brazil', 'Herold', 'Heggs', 44),\n",
    "('Latvia', 'Verney', 'Note', 50),\n",
    "('Poland', 'Temp', 'Ribey', 50),\n",
    "('China', 'Conroy', 'Egdal', 48),\n",
    "('Japan', 'Gabie', 'Alessandone', 47),\n",
    "('Ukraine', 'Devlen', 'Chaperlin', 54),\n",
    "('France', 'Babbette', 'Turner', 51),\n",
    "('Czech Republic', 'Virgil', 'Scotney', 52),\n",
    "('Tajikistan', 'Zorina', 'Bedow', 49),\n",
    "('China', 'Aidan', 'Rudeyeard', 50),\n",
    "('Ireland', 'Saunder', 'MacLice', 48),\n",
    "('France', 'Waly', 'Brunstan', 53),\n",
    "('China', 'Gisele', 'Enns', 52),\n",
    "('Peru', 'Mina', 'Winchester', 48),\n",
    "('Japan', 'Torie', 'MacShirrie', 50),\n",
    "('Russia', 'Benjamen', 'Kenford', 51),\n",
    "('China', 'Etan', 'Burn', 53),\n",
    "('Russia', 'Merralee', 'Chaperlin', 38),\n",
    "('Indonesia', 'Lanny', 'Malam', 49),\n",
    "('Canada', 'Wilhelm', 'Deeprose', 54),\n",
    "('Czech Republic', 'Lari', 'Hillhouse', 48),\n",
    "('China', 'Ossie', 'Woodley', 52),\n",
    "('Macedonia', 'April', 'Tyer', 50),\n",
    "('Vietnam', 'Madelon', 'Dansey', 53),\n",
    "('Ukraine', 'Korella', 'McNamee', 52),\n",
    "('Jamaica', 'Linnea', 'Cannam', 43),\n",
    "('China', 'Mart', 'Coling', 52),\n",
    "('Indonesia', 'Marna', 'Causbey', 47),\n",
    "('China', 'Berni', 'Daintier', 55),\n",
    "('Poland', 'Cynthia', 'Hassell', 49),\n",
    "('Canada', 'Carma', 'Schule', 49),\n",
    "('Indonesia', 'Malia', 'Blight', 48),\n",
    "('China', 'Paulo', 'Seivertsen', 47),\n",
    "('Niger', 'Kaylee', 'Hearley', 54),\n",
    "('Japan', 'Maure', 'Jandak', 46),\n",
    "('Argentina', 'Foss', 'Feavers', 45),\n",
    "('Venezuela', 'Ron', 'Leggitt', 60),\n",
    "('Russia', 'Flint', 'Gokes', 40),\n",
    "('China', 'Linet', 'Conelly', 52),\n",
    "('Philippines', 'Nikolas', 'Birtwell', 57),\n",
    "('Australia', 'Eduard', 'Leipelt', 53)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Using Python Variables in your SQL Statements\n",
    "\n",
    "##### You can use python variables in your SQL statements by adding a \":\" prefix to your python variable names.\n",
    "\n",
    "##### For example, if I have a python variable `country` with a value of `\"Canada\"`, I can use this variable in a SQL query to find all the rows of students from Canada.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///SQLiteMagic.db\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>country</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>test_score</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Canada</td>\n",
       "            <td>Cristionna</td>\n",
       "            <td>Wadmore</td>\n",
       "            <td>46</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Canada</td>\n",
       "            <td>Wilhelm</td>\n",
       "            <td>Deeprose</td>\n",
       "            <td>54</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Canada</td>\n",
       "            <td>Carma</td>\n",
       "            <td>Schule</td>\n",
       "            <td>49</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Canada', 'Cristionna', 'Wadmore', 46),\n",
       " ('Canada', 'Wilhelm', 'Deeprose', 54),\n",
       " ('Canada', 'Carma', 'Schule', 49)]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country = \"Canada\"\n",
    "%sql select * from INTERNATIONAL_STUDENT_TEST_SCORES where country = :country"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Assigning the Results of Queries to Python Variables\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### You can use the normal python assignment syntax to assign the results of your queries to python variables.\n",
    "\n",
    "##### For example, I have a SQL query to retrieve the distribution of test scores (i.e. how many students got each score). I can assign the result of this query to the variable `test_score_distribution` using the `=` operator.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///SQLiteMagic.db\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>Test_Score</th>\n",
       "            <th>Frequency</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>38</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>40</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>43</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>44</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>45</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>46</td>\n",
       "            <td>7</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>47</td>\n",
       "            <td>4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>48</td>\n",
       "            <td>14</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>49</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>50</td>\n",
       "            <td>10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>51</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>52</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>53</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>54</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>55</td>\n",
       "            <td>4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>56</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>57</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>58</td>\n",
       "            <td>4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>60</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(38, 2),\n",
       " (40, 1),\n",
       " (43, 2),\n",
       " (44, 2),\n",
       " (45, 8),\n",
       " (46, 7),\n",
       " (47, 4),\n",
       " (48, 14),\n",
       " (49, 8),\n",
       " (50, 10),\n",
       " (51, 8),\n",
       " (52, 8),\n",
       " (53, 8),\n",
       " (54, 5),\n",
       " (55, 4),\n",
       " (56, 1),\n",
       " (57, 2),\n",
       " (58, 4),\n",
       " (60, 1)]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_score_distribution = %sql SELECT test_score as \"Test_Score\", count(*) as \"Frequency\" from INTERNATIONAL_STUDENT_TEST_SCORES GROUP BY test_score;\n",
    "test_score_distribution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Converting Query Results to DataFrames\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### You can easily convert a SQL query result to a pandas dataframe using the `DataFrame()` method. Dataframe objects are much more versatile than SQL query result objects. For example, we can easily graph our test score distribution after converting to a dataframe.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataframe = test_score_distribution.DataFrame()\n",
    "\n",
    "%matplotlib inline\n",
    "# uncomment the following line if you get an module error saying seaborn not found\n",
    "# !pip install seaborn==0.9.0\n",
    "import seaborn\n",
    "\n",
    "plot = seaborn.barplot(x='Test_Score',y='Frequency', data=dataframe)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now you know how to work with Db2 from within JupyterLab notebooks using SQL \"magic\"!\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///SQLiteMagic.db\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>country</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>test_score</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>United States</td>\n",
       "            <td>Marshall</td>\n",
       "            <td>Bernadot</td>\n",
       "            <td>54</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Ghana</td>\n",
       "            <td>Celinda</td>\n",
       "            <td>Malkin</td>\n",
       "            <td>51</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Ukraine</td>\n",
       "            <td>Guillermo</td>\n",
       "            <td>Furze</td>\n",
       "            <td>53</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Greece</td>\n",
       "            <td>Aharon</td>\n",
       "            <td>Tunnow</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Russia</td>\n",
       "            <td>Bail</td>\n",
       "            <td>Goodwin</td>\n",
       "            <td>46</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Poland</td>\n",
       "            <td>Cole</td>\n",
       "            <td>Winteringham</td>\n",
       "            <td>49</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Sweden</td>\n",
       "            <td>Emlyn</td>\n",
       "            <td>Erricker</td>\n",
       "            <td>55</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Russia</td>\n",
       "            <td>Cathee</td>\n",
       "            <td>Sivewright</td>\n",
       "            <td>49</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Barny</td>\n",
       "            <td>Ingerson</td>\n",
       "            <td>57</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Uganda</td>\n",
       "            <td>Sharla</td>\n",
       "            <td>Papaccio</td>\n",
       "            <td>55</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Stella</td>\n",
       "            <td>Youens</td>\n",
       "            <td>51</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Poland</td>\n",
       "            <td>Julio</td>\n",
       "            <td>Buesden</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United States</td>\n",
       "            <td>Tiffie</td>\n",
       "            <td>Cosely</td>\n",
       "            <td>58</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Poland</td>\n",
       "            <td>Auroora</td>\n",
       "            <td>Stiffell</td>\n",
       "            <td>45</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Clarita</td>\n",
       "            <td>Huet</td>\n",
       "            <td>52</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Poland</td>\n",
       "            <td>Shannon</td>\n",
       "            <td>Goulden</td>\n",
       "            <td>45</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Philippines</td>\n",
       "            <td>Emylee</td>\n",
       "            <td>Privost</td>\n",
       "            <td>50</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>France</td>\n",
       "            <td>Madelina</td>\n",
       "            <td>Burk</td>\n",
       "            <td>49</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Saunderson</td>\n",
       "            <td>Root</td>\n",
       "            <td>58</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Indonesia</td>\n",
       "            <td>Bo</td>\n",
       "            <td>Waring</td>\n",
       "            <td>55</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Hollis</td>\n",
       "            <td>Domotor</td>\n",
       "            <td>45</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Russia</td>\n",
       "            <td>Robbie</td>\n",
       "            <td>Collip</td>\n",
       "            <td>46</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Philippines</td>\n",
       "            <td>Davon</td>\n",
       "            <td>Donisi</td>\n",
       "            <td>46</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Cristabel</td>\n",
       "            <td>Radeliffe</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Wallis</td>\n",
       "            <td>Bartleet</td>\n",
       "            <td>58</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Moldova</td>\n",
       "            <td>Arleen</td>\n",
       "            <td>Stailey</td>\n",
       "            <td>38</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Ireland</td>\n",
       "            <td>Mendel</td>\n",
       "            <td>Grumble</td>\n",
       "            <td>58</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Sallyann</td>\n",
       "            <td>Exley</td>\n",
       "            <td>51</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Mexico</td>\n",
       "            <td>Kain</td>\n",
       "            <td>Swaite</td>\n",
       "            <td>46</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Indonesia</td>\n",
       "            <td>Alonso</td>\n",
       "            <td>Bulteel</td>\n",
       "            <td>45</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Armenia</td>\n",
       "            <td>Anatol</td>\n",
       "            <td>Tankus</td>\n",
       "            <td>51</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Indonesia</td>\n",
       "            <td>Coralyn</td>\n",
       "            <td>Dawkins</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Deanne</td>\n",
       "            <td>Edwinson</td>\n",
       "            <td>45</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Georgiana</td>\n",
       "            <td>Epple</td>\n",
       "            <td>51</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Portugal</td>\n",
       "            <td>Bartlet</td>\n",
       "            <td>Breese</td>\n",
       "            <td>56</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Azerbaijan</td>\n",
       "            <td>Idalina</td>\n",
       "            <td>Lukash</td>\n",
       "            <td>50</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>France</td>\n",
       "            <td>Livvie</td>\n",
       "            <td>Flory</td>\n",
       "            <td>54</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Malaysia</td>\n",
       "            <td>Nonie</td>\n",
       "            <td>Borit</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Indonesia</td>\n",
       "            <td>Clio</td>\n",
       "            <td>Mugg</td>\n",
       "            <td>47</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Brazil</td>\n",
       "            <td>Westley</td>\n",
       "            <td>Measor</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Philippines</td>\n",
       "            <td>Katrinka</td>\n",
       "            <td>Sibbert</td>\n",
       "            <td>51</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Poland</td>\n",
       "            <td>Valentia</td>\n",
       "            <td>Mounch</td>\n",
       "            <td>50</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Norway</td>\n",
       "            <td>Sheilah</td>\n",
       "            <td>Hedditch</td>\n",
       "            <td>53</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Papua New Guinea</td>\n",
       "            <td>Itch</td>\n",
       "            <td>Jubb</td>\n",
       "            <td>50</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Latvia</td>\n",
       "            <td>Stesha</td>\n",
       "            <td>Garnson</td>\n",
       "            <td>53</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Canada</td>\n",
       "            <td>Cristionna</td>\n",
       "            <td>Wadmore</td>\n",
       "            <td>46</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Lianna</td>\n",
       "            <td>Gatward</td>\n",
       "            <td>43</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Guatemala</td>\n",
       "            <td>Tanney</td>\n",
       "            <td>Vials</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>France</td>\n",
       "            <td>Alma</td>\n",
       "            <td>Zavittieri</td>\n",
       "            <td>44</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Alvira</td>\n",
       "            <td>Tamas</td>\n",
       "            <td>50</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United States</td>\n",
       "            <td>Shanon</td>\n",
       "            <td>Peres</td>\n",
       "            <td>45</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Sweden</td>\n",
       "            <td>Maisey</td>\n",
       "            <td>Lynas</td>\n",
       "            <td>53</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Indonesia</td>\n",
       "            <td>Kip</td>\n",
       "            <td>Hothersall</td>\n",
       "            <td>46</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Cash</td>\n",
       "            <td>Landis</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Panama</td>\n",
       "            <td>Kennith</td>\n",
       "            <td>Digance</td>\n",
       "            <td>45</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Ulberto</td>\n",
       "            <td>Riggeard</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Switzerland</td>\n",
       "            <td>Judy</td>\n",
       "            <td>Gilligan</td>\n",
       "            <td>49</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Philippines</td>\n",
       "            <td>Tod</td>\n",
       "            <td>Trevaskus</td>\n",
       "            <td>52</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Brazil</td>\n",
       "            <td>Herold</td>\n",
       "            <td>Heggs</td>\n",
       "            <td>44</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Latvia</td>\n",
       "            <td>Verney</td>\n",
       "            <td>Note</td>\n",
       "            <td>50</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Poland</td>\n",
       "            <td>Temp</td>\n",
       "            <td>Ribey</td>\n",
       "            <td>50</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Conroy</td>\n",
       "            <td>Egdal</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Japan</td>\n",
       "            <td>Gabie</td>\n",
       "            <td>Alessandone</td>\n",
       "            <td>47</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Ukraine</td>\n",
       "            <td>Devlen</td>\n",
       "            <td>Chaperlin</td>\n",
       "            <td>54</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>France</td>\n",
       "            <td>Babbette</td>\n",
       "            <td>Turner</td>\n",
       "            <td>51</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Czech Republic</td>\n",
       "            <td>Virgil</td>\n",
       "            <td>Scotney</td>\n",
       "            <td>52</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Tajikistan</td>\n",
       "            <td>Zorina</td>\n",
       "            <td>Bedow</td>\n",
       "            <td>49</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Aidan</td>\n",
       "            <td>Rudeyeard</td>\n",
       "            <td>50</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Ireland</td>\n",
       "            <td>Saunder</td>\n",
       "            <td>MacLice</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>France</td>\n",
       "            <td>Waly</td>\n",
       "            <td>Brunstan</td>\n",
       "            <td>53</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Gisele</td>\n",
       "            <td>Enns</td>\n",
       "            <td>52</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Peru</td>\n",
       "            <td>Mina</td>\n",
       "            <td>Winchester</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Japan</td>\n",
       "            <td>Torie</td>\n",
       "            <td>MacShirrie</td>\n",
       "            <td>50</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Russia</td>\n",
       "            <td>Benjamen</td>\n",
       "            <td>Kenford</td>\n",
       "            <td>51</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Etan</td>\n",
       "            <td>Burn</td>\n",
       "            <td>53</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Russia</td>\n",
       "            <td>Merralee</td>\n",
       "            <td>Chaperlin</td>\n",
       "            <td>38</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Indonesia</td>\n",
       "            <td>Lanny</td>\n",
       "            <td>Malam</td>\n",
       "            <td>49</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Canada</td>\n",
       "            <td>Wilhelm</td>\n",
       "            <td>Deeprose</td>\n",
       "            <td>54</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Czech Republic</td>\n",
       "            <td>Lari</td>\n",
       "            <td>Hillhouse</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Ossie</td>\n",
       "            <td>Woodley</td>\n",
       "            <td>52</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Macedonia</td>\n",
       "            <td>April</td>\n",
       "            <td>Tyer</td>\n",
       "            <td>50</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Vietnam</td>\n",
       "            <td>Madelon</td>\n",
       "            <td>Dansey</td>\n",
       "            <td>53</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Ukraine</td>\n",
       "            <td>Korella</td>\n",
       "            <td>McNamee</td>\n",
       "            <td>52</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Jamaica</td>\n",
       "            <td>Linnea</td>\n",
       "            <td>Cannam</td>\n",
       "            <td>43</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Mart</td>\n",
       "            <td>Coling</td>\n",
       "            <td>52</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Indonesia</td>\n",
       "            <td>Marna</td>\n",
       "            <td>Causbey</td>\n",
       "            <td>47</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Berni</td>\n",
       "            <td>Daintier</td>\n",
       "            <td>55</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Poland</td>\n",
       "            <td>Cynthia</td>\n",
       "            <td>Hassell</td>\n",
       "            <td>49</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Canada</td>\n",
       "            <td>Carma</td>\n",
       "            <td>Schule</td>\n",
       "            <td>49</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Indonesia</td>\n",
       "            <td>Malia</td>\n",
       "            <td>Blight</td>\n",
       "            <td>48</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Paulo</td>\n",
       "            <td>Seivertsen</td>\n",
       "            <td>47</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Niger</td>\n",
       "            <td>Kaylee</td>\n",
       "            <td>Hearley</td>\n",
       "            <td>54</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Japan</td>\n",
       "            <td>Maure</td>\n",
       "            <td>Jandak</td>\n",
       "            <td>46</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Argentina</td>\n",
       "            <td>Foss</td>\n",
       "            <td>Feavers</td>\n",
       "            <td>45</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Venezuela</td>\n",
       "            <td>Ron</td>\n",
       "            <td>Leggitt</td>\n",
       "            <td>60</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Russia</td>\n",
       "            <td>Flint</td>\n",
       "            <td>Gokes</td>\n",
       "            <td>40</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>Linet</td>\n",
       "            <td>Conelly</td>\n",
       "            <td>52</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Philippines</td>\n",
       "            <td>Nikolas</td>\n",
       "            <td>Birtwell</td>\n",
       "            <td>57</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Australia</td>\n",
       "            <td>Eduard</td>\n",
       "            <td>Leipelt</td>\n",
       "            <td>53</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('United States', 'Marshall', 'Bernadot', 54),\n",
       " ('Ghana', 'Celinda', 'Malkin', 51),\n",
       " ('Ukraine', 'Guillermo', 'Furze', 53),\n",
       " ('Greece', 'Aharon', 'Tunnow', 48),\n",
       " ('Russia', 'Bail', 'Goodwin', 46),\n",
       " ('Poland', 'Cole', 'Winteringham', 49),\n",
       " ('Sweden', 'Emlyn', 'Erricker', 55),\n",
       " ('Russia', 'Cathee', 'Sivewright', 49),\n",
       " ('China', 'Barny', 'Ingerson', 57),\n",
       " ('Uganda', 'Sharla', 'Papaccio', 55),\n",
       " ('China', 'Stella', 'Youens', 51),\n",
       " ('Poland', 'Julio', 'Buesden', 48),\n",
       " ('United States', 'Tiffie', 'Cosely', 58),\n",
       " ('Poland', 'Auroora', 'Stiffell', 45),\n",
       " ('China', 'Clarita', 'Huet', 52),\n",
       " ('Poland', 'Shannon', 'Goulden', 45),\n",
       " ('Philippines', 'Emylee', 'Privost', 50),\n",
       " ('France', 'Madelina', 'Burk', 49),\n",
       " ('China', 'Saunderson', 'Root', 58),\n",
       " ('Indonesia', 'Bo', 'Waring', 55),\n",
       " ('China', 'Hollis', 'Domotor', 45),\n",
       " ('Russia', 'Robbie', 'Collip', 46),\n",
       " ('Philippines', 'Davon', 'Donisi', 46),\n",
       " ('China', 'Cristabel', 'Radeliffe', 48),\n",
       " ('China', 'Wallis', 'Bartleet', 58),\n",
       " ('Moldova', 'Arleen', 'Stailey', 38),\n",
       " ('Ireland', 'Mendel', 'Grumble', 58),\n",
       " ('China', 'Sallyann', 'Exley', 51),\n",
       " ('Mexico', 'Kain', 'Swaite', 46),\n",
       " ('Indonesia', 'Alonso', 'Bulteel', 45),\n",
       " ('Armenia', 'Anatol', 'Tankus', 51),\n",
       " ('Indonesia', 'Coralyn', 'Dawkins', 48),\n",
       " ('China', 'Deanne', 'Edwinson', 45),\n",
       " ('China', 'Georgiana', 'Epple', 51),\n",
       " ('Portugal', 'Bartlet', 'Breese', 56),\n",
       " ('Azerbaijan', 'Idalina', 'Lukash', 50),\n",
       " ('France', 'Livvie', 'Flory', 54),\n",
       " ('Malaysia', 'Nonie', 'Borit', 48),\n",
       " ('Indonesia', 'Clio', 'Mugg', 47),\n",
       " ('Brazil', 'Westley', 'Measor', 48),\n",
       " ('Philippines', 'Katrinka', 'Sibbert', 51),\n",
       " ('Poland', 'Valentia', 'Mounch', 50),\n",
       " ('Norway', 'Sheilah', 'Hedditch', 53),\n",
       " ('Papua New Guinea', 'Itch', 'Jubb', 50),\n",
       " ('Latvia', 'Stesha', 'Garnson', 53),\n",
       " ('Canada', 'Cristionna', 'Wadmore', 46),\n",
       " ('China', 'Lianna', 'Gatward', 43),\n",
       " ('Guatemala', 'Tanney', 'Vials', 48),\n",
       " ('France', 'Alma', 'Zavittieri', 44),\n",
       " ('China', 'Alvira', 'Tamas', 50),\n",
       " ('United States', 'Shanon', 'Peres', 45),\n",
       " ('Sweden', 'Maisey', 'Lynas', 53),\n",
       " ('Indonesia', 'Kip', 'Hothersall', 46),\n",
       " ('China', 'Cash', 'Landis', 48),\n",
       " ('Panama', 'Kennith', 'Digance', 45),\n",
       " ('China', 'Ulberto', 'Riggeard', 48),\n",
       " ('Switzerland', 'Judy', 'Gilligan', 49),\n",
       " ('Philippines', 'Tod', 'Trevaskus', 52),\n",
       " ('Brazil', 'Herold', 'Heggs', 44),\n",
       " ('Latvia', 'Verney', 'Note', 50),\n",
       " ('Poland', 'Temp', 'Ribey', 50),\n",
       " ('China', 'Conroy', 'Egdal', 48),\n",
       " ('Japan', 'Gabie', 'Alessandone', 47),\n",
       " ('Ukraine', 'Devlen', 'Chaperlin', 54),\n",
       " ('France', 'Babbette', 'Turner', 51),\n",
       " ('Czech Republic', 'Virgil', 'Scotney', 52),\n",
       " ('Tajikistan', 'Zorina', 'Bedow', 49),\n",
       " ('China', 'Aidan', 'Rudeyeard', 50),\n",
       " ('Ireland', 'Saunder', 'MacLice', 48),\n",
       " ('France', 'Waly', 'Brunstan', 53),\n",
       " ('China', 'Gisele', 'Enns', 52),\n",
       " ('Peru', 'Mina', 'Winchester', 48),\n",
       " ('Japan', 'Torie', 'MacShirrie', 50),\n",
       " ('Russia', 'Benjamen', 'Kenford', 51),\n",
       " ('China', 'Etan', 'Burn', 53),\n",
       " ('Russia', 'Merralee', 'Chaperlin', 38),\n",
       " ('Indonesia', 'Lanny', 'Malam', 49),\n",
       " ('Canada', 'Wilhelm', 'Deeprose', 54),\n",
       " ('Czech Republic', 'Lari', 'Hillhouse', 48),\n",
       " ('China', 'Ossie', 'Woodley', 52),\n",
       " ('Macedonia', 'April', 'Tyer', 50),\n",
       " ('Vietnam', 'Madelon', 'Dansey', 53),\n",
       " ('Ukraine', 'Korella', 'McNamee', 52),\n",
       " ('Jamaica', 'Linnea', 'Cannam', 43),\n",
       " ('China', 'Mart', 'Coling', 52),\n",
       " ('Indonesia', 'Marna', 'Causbey', 47),\n",
       " ('China', 'Berni', 'Daintier', 55),\n",
       " ('Poland', 'Cynthia', 'Hassell', 49),\n",
       " ('Canada', 'Carma', 'Schule', 49),\n",
       " ('Indonesia', 'Malia', 'Blight', 48),\n",
       " ('China', 'Paulo', 'Seivertsen', 47),\n",
       " ('Niger', 'Kaylee', 'Hearley', 54),\n",
       " ('Japan', 'Maure', 'Jandak', 46),\n",
       " ('Argentina', 'Foss', 'Feavers', 45),\n",
       " ('Venezuela', 'Ron', 'Leggitt', 60),\n",
       " ('Russia', 'Flint', 'Gokes', 40),\n",
       " ('China', 'Linet', 'Conelly', 52),\n",
       " ('Philippines', 'Nikolas', 'Birtwell', 57),\n",
       " ('Australia', 'Eduard', 'Leipelt', 53)]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "\n",
    "-- Feel free to experiment with the data set provided in this notebook for practice:\n",
    "SELECT country, first_name, last_name, test_score FROM INTERNATIONAL_STUDENT_TEST_SCORES;    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Author\n",
    "\n",
    "<a href=\"https://www.linkedin.com/in/ravahuja/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkDB0201ENSkillsNetwork20127838-2022-01-01\" target=\"_blank\">Rav Ahuja</a>\n",
    "\n",
    "<a href=\"https://www.linkedin.com/in/lakshmi-holla-b39062149/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkDB0201ENSkillsNetwork20127838-2022-01-01\" target=\"_blank\">Lakshmi Holla</a>\n",
    "\n",
    "## Other Contributor(s)\n",
    "\n",
    "<a href=\"https://www.linkedin.com/in/malika-goyal-04798622/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkDB0201ENSkillsNetwork20127838-2022-01-01\" target=\"_blank\">Malika</a>\n",
    "\n",
    "## Change Log\n",
    "\n",
    "| Date (YYYY-MM-DD) | Version | Changed By    | Change Description        |\n",
    "| ----------------- | ------- | ------------- | ------------------------- |\n",
    "| 2022-03-04        | 1.0     | Lakshmi Holla | Created lab using sqlite3 |\n",
    "\n",
    "<hr>\n",
    "\n",
    "## <h3 align=\"center\"> © IBM Corporation 2022. All rights reserved. <h3/>\n"
   ]
  }
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