4) Exploratory_Data_Analysis_Sql .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-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork865-2022-01-01\" 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",
    "<h1 align=center><font size = 5>Assignment: SQL Notebook for Peer Assignment</font></h1>\n",
    "\n",
    "Estimated time needed: **60** minutes.\n",
    "\n",
    "## Introduction\n",
    "Using this Python notebook you will:\n",
    "\n",
    "1.  Understand the Spacex DataSet\n",
    "2.  Load the dataset  into the corresponding table in a Db2 database\n",
    "3.  Execute SQL queries to answer assignment questions \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview of the DataSet\n",
    "\n",
    "SpaceX has gained worldwide attention for a series of historic milestones. \n",
    "\n",
    "It is the only private company ever to return a spacecraft from low-earth orbit, which it first accomplished in December 2010.\n",
    "SpaceX advertises Falcon 9 rocket launches on its website with a cost of 62 million dollars wheras other providers cost upward of 165 million dollars each, much of the savings is because Space X can reuse the first stage. \n",
    "\n",
    "\n",
    "Therefore if we can determine if the first stage will land, we can determine the cost of a launch. \n",
    "\n",
    "This information can be used if an alternate company wants to bid against SpaceX for a rocket launch.\n",
    "\n",
    "This dataset includes a record for each payload carried during a SpaceX mission into outer space.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Download the datasets\n",
    "\n",
    "This assignment requires you to load the spacex dataset.\n",
    "\n",
    "In many cases the dataset to be analyzed is available as a .CSV (comma separated values) file, perhaps on the internet. Click on the link below to download and save the dataset (.CSV file):\n",
    "\n",
    " <a href=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/labs/module_2/data/Spacex.csv\" target=\"_blank\">Spacex DataSet</a>\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: sqlalchemy==1.3.9 in /home/jupyterlab/conda/envs/python/lib/python3.7/site-packages (1.3.9)\n"
     ]
    }
   ],
   "source": [
    "!pip install sqlalchemy==1.3.9\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Connect to the database\n",
    "\n",
    "Let us first load the SQL extension and establish a connection with the database\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv, sqlite3\n",
    "\n",
    "con = sqlite3.connect(\"pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain\")\n",
    "cur = con.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install -q pandas==1.1.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Connected: @pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain'"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql sqlite:///pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv(\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/labs/module_2/data/Spacex.csv\")\n",
    "df.to_sql(\"SPACEXTBL\", con, if_exists='replace', index=False,method=\"multi\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# SERVICE CREDENTIAL - %sql ibm_db_sa://pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tasks\n",
    "\n",
    "Now write and execute SQL queries to solve the assignment tasks.\n",
    "\n",
    "**Note: If the column names are in mixed case enclose it in double quotes\n",
    "   For Example \"Landing_Outcome\"**\n",
    "\n",
    "### Task 1\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "##### Display the names of the unique launch sites  in the space mission\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain\n",
      "(sqlite3.OperationalError) near \"UNIQUE\": syntax error\n",
      "[SQL: SELECT UNIQUE(LAUNCH_SITE) FROM SPACEXTBL;]\n",
      "(Background on this error at: http://sqlalche.me/e/e3q8)\n"
     ]
    }
   ],
   "source": [
    "%sql SELECT UNIQUE(LAUNCH_SITE) FROM SPACEXTBL;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Task 2\n",
    "\n",
    "\n",
    "#####  Display 5 records where launch sites begin with the string 'CCA' \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>Launch_Site</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>CCAFS LC-40</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>CCAFS LC-40</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>CCAFS LC-40</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>CCAFS LC-40</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>CCAFS LC-40</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('CCAFS LC-40',),\n",
       " ('CCAFS LC-40',),\n",
       " ('CCAFS LC-40',),\n",
       " ('CCAFS LC-40',),\n",
       " ('CCAFS LC-40',)]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT LAUNCH_SITE FROM SPACEXTBL WHERE LAUNCH_SITE LIKE 'CCA%' LIMIT 5;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 3\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "##### Display the total payload mass carried by boosters launched by NASA (CRS)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>TOTAL_PAYLOAD_MASS</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>45596.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(45596.0,)]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT SUM(PAYLOAD_MASS__KG_) AS TOTAL_PAYLOAD_MASS FROM SPACEXTBL \\\n",
    "    WHERE CUSTOMER = 'NASA (CRS)';"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 4\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "##### Display average payload mass carried by booster version F9 v1.1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>AVERAGE_PAYLOAD_MASS</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>2928.4</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(2928.4,)]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT AVG(PAYLOAD_MASS__KG_) AS AVERAGE_PAYLOAD_MASS FROM SPACEXTBL \\\n",
    "    WHERE BOOSTER_VERSION = 'F9 v1.1';"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 5\n",
    "\n",
    "##### List the date when the first succesful landing outcome in ground pad was acheived.\n",
    "\n",
    "\n",
    "_Hint:Use min function_ \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain\n",
      "(sqlite3.OperationalError) no such column: LANDING__OUTCOME\n",
      "[SQL: SELECT MIN(DATE) AS FIRST_SUCCESSFUL_GROUND_LANDING FROM SPACEXTBL      WHERE LANDING__OUTCOME = 'Success (ground pad)';]\n",
      "(Background on this error at: http://sqlalche.me/e/e3q8)\n"
     ]
    }
   ],
   "source": [
    "%sql SELECT MIN(DATE) AS FIRST_SUCCESSFUL_GROUND_LANDING FROM SPACEXTBL \\\n",
    "    WHERE LANDING__OUTCOME = 'Success (ground pad)';"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 6\n",
    "\n",
    "##### List the names of the boosters which have success in drone ship and have payload mass greater than 4000 but less than 6000\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain\n",
      "(sqlite3.OperationalError) no such column: LANDING__OUTCOME\n",
      "[SQL: SELECT BOOSTER_VERSION FROM SPACEXTBL      WHERE (LANDING__OUTCOME = 'Success (drone ship)') AND (PAYLOAD_MASS__KG_ BETWEEN 4000 AND 6000);]\n",
      "(Background on this error at: http://sqlalche.me/e/e3q8)\n"
     ]
    }
   ],
   "source": [
    "%sql SELECT BOOSTER_VERSION FROM SPACEXTBL \\\n",
    "    WHERE (LANDING__OUTCOME = 'Success (drone ship)') AND (PAYLOAD_MASS__KG_ BETWEEN 4000 AND 6000);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 7\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "##### List the total number of successful and failure mission outcomes\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>Mission_Outcome</th>\n",
       "            <th>TOTAL_NUMBER</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>None</td>\n",
       "            <td>0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Failure (in flight)</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Success</td>\n",
       "            <td>98</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Success </td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Success (payload status unclear)</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(None, 0),\n",
       " ('Failure (in flight)', 1),\n",
       " ('Success', 98),\n",
       " ('Success ', 1),\n",
       " ('Success (payload status unclear)', 1)]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT MISSION_OUTCOME, COUNT(MISSION_OUTCOME) AS TOTAL_NUMBER FROM SPACEXTBL GROUP BY MISSION_OUTCOME;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 8\n",
    "\n",
    "\n",
    "\n",
    "##### List the   names of the booster_versions which have carried the maximum payload mass. Use a subquery\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>Booster_Version</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>F9 B5 B1048.4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>F9 B5 B1049.4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>F9 B5 B1051.3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>F9 B5 B1056.4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>F9 B5 B1048.5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>F9 B5 B1051.4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>F9 B5 B1049.5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>F9 B5 B1060.2 </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>F9 B5 B1058.3 </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>F9 B5 B1051.6</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>F9 B5 B1060.3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>F9 B5 B1049.7 </td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('F9 B5 B1048.4',),\n",
       " ('F9 B5 B1049.4',),\n",
       " ('F9 B5 B1051.3',),\n",
       " ('F9 B5 B1056.4',),\n",
       " ('F9 B5 B1048.5',),\n",
       " ('F9 B5 B1051.4',),\n",
       " ('F9 B5 B1049.5',),\n",
       " ('F9 B5 B1060.2 ',),\n",
       " ('F9 B5 B1058.3 ',),\n",
       " ('F9 B5 B1051.6',),\n",
       " ('F9 B5 B1060.3',),\n",
       " ('F9 B5 B1049.7 ',)]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT DISTINCT(BOOSTER_VERSION) FROM SPACEXTBL \\\n",
    "    WHERE PAYLOAD_MASS__KG_ = (SELECT MAX(PAYLOAD_MASS__KG_) FROM SPACEXTBL);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 9\n",
    "\n",
    "\n",
    "##### List the records which will display the month names, failure landing_outcomes in drone ship ,booster versions, launch_site for the months in year 2015.\n",
    "\n",
    "**Note: SQLLite does not support monthnames. So you need to use  substr(Date, 4, 2) as month to get the months and substr(Date,7,4)='2015' for year.**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain\n",
      "(sqlite3.OperationalError) near \"FROM\": syntax error\n",
      "[SQL: SELECT BOOSTER_VERSION, LAUNCH_SITE FROM SPACEXTBL      WHERE (LANDING__OUTCOME = 'Failure (drone ship)') AND (EXTRACT(YEAR FROM DATE) = '2015');]\n",
      "(Background on this error at: http://sqlalche.me/e/e3q8)\n"
     ]
    }
   ],
   "source": [
    "%sql SELECT BOOSTER_VERSION, LAUNCH_SITE FROM SPACEXTBL \\\n",
    "    WHERE (LANDING__OUTCOME = 'Failure (drone ship)') AND (EXTRACT(YEAR FROM DATE) = '2015');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 10\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "##### Rank the  count of  successful landing_outcomes between the date 04-06-2010 and 20-03-2017 in descending order.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///pyt40448:8M8YAelxPjqJwjVy@19af6446-6171-4641-8aba-9dcff8e1b6ff.c1ogj3sd0tgtu0lqde00.databases.appdomain\n",
      "(sqlite3.OperationalError) no such column: LANDING__OUTCOME\n",
      "[SQL: SELECT LANDING__OUTCOME, COUNT(LANDING__OUTCOME) AS TOTAL_NUMBER FROM SPACEXTBL      WHERE DATE BETWEEN '2010-06-04' AND '2017-03-20'      GROUP BY LANDING__OUTCOME      ORDER BY TOTAL_NUMBER DESC;]\n",
      "(Background on this error at: http://sqlalche.me/e/e3q8)\n"
     ]
    }
   ],
   "source": [
    "%sql SELECT LANDING__OUTCOME, COUNT(LANDING__OUTCOME) AS TOTAL_NUMBER FROM SPACEXTBL \\\n",
    "    WHERE DATE BETWEEN '2010-06-04' AND '2017-03-20' \\\n",
    "    GROUP BY LANDING__OUTCOME \\\n",
    "    ORDER BY TOTAL_NUMBER DESC;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reference Links\n",
    "\n",
    "* <a href =\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DB0201EN-SkillsNetwork/labs/Labs_Coursera_V5/labs/Lab%20-%20String%20Patterns%20-%20Sorting%20-%20Grouping/instructional-labs.md.html?origin=www.coursera.org\">Hands-on Lab : String Patterns, Sorting and Grouping</a>  \n",
    "\n",
    "*  <a  href=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DB0201EN-SkillsNetwork/labs/Labs_Coursera_V5/labs/Lab%20-%20Built-in%20functions%20/Hands-on_Lab__Built-in_Functions.md.html?origin=www.coursera.org\">Hands-on Lab: Built-in functions</a>\n",
    "\n",
    "*  <a  href=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DB0201EN-SkillsNetwork/labs/Labs_Coursera_V5/labs/Lab%20-%20Sub-queries%20and%20Nested%20SELECTs%20/instructional-labs.md.html?origin=www.coursera.org\">Hands-on Lab : Sub-queries and Nested SELECT Statements</a>\n",
    "\n",
    "*   <a href=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DB0201EN-SkillsNetwork/labs/Module%205/DB0201EN-Week3-1-3-SQLmagic.ipynb\">Hands-on Tutorial: Accessing Databases with SQL magic</a>\n",
    "\n",
    "*  <a href= \"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DB0201EN-SkillsNetwork/labs/Module%205/DB0201EN-Week3-1-4-Analyzing.ipynb\">Hands-on Lab: Analyzing a real World Data Set</a>\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Author(s)\n",
    "\n",
    "<h4> Lakshmi Holla </h4>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Other Contributors\n",
    "\n",
    "<h4> Rav Ahuja </h4>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Change log\n",
    "| Date | Version | Changed by | Change Description |\n",
    "|------|--------|--------|---------|\n",
    "| 2021-07-09 | 0.2 |Lakshmi Holla | Changes made in magic sql|\n",
    "| 2021-05-20 | 0.1 |Lakshmi Holla | Created Initial Version |\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <h3 align=\"center\"> © IBM Corporation 2021. All rights reserved. <h3/>\n"
   ]
  }
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