02_EDA_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-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2022-01-01\" 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",
    "\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",
    "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?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2022-01-01\" target=\"_blank\">Spacex DataSet</a>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Store the dataset in database table\n",
    "\n",
    "**it is highly recommended to manually load the table using the database console LOAD tool in DB2**.\n",
    "\n",
    "<img src = \"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/labs/module_2/images/spacexload.png\">\n",
    "\n",
    "Now open the Db2 console, open the LOAD tool, Select / Drag the .CSV file for the  dataset, Next create a New Table, and then follow the steps on-screen instructions to load the data. Name the new table as follows:\n",
    "\n",
    "**SPACEXDATASET**\n",
    "\n",
    "**Follow these steps while using old DB2 UI which is having Open Console Screen**\n",
    "\n",
    "**Note:While loading Spacex dataset, ensure that detect datatypes is disabled. Later click on the pencil icon(edit option).**\n",
    "\n",
    "1.  Change the Date Format by manually typing DD-MM-YYYY and timestamp format as DD-MM-YYYY HH\\:MM:SS\n",
    "\n",
    "2.  Change the PAYLOAD_MASS\\_\\_KG\\_  datatype  to INTEGER.\n",
    "\n",
    "<img src = \"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/labs/module_2/images/spacexload2.png\">\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Changes to be considered when having DB2 instance with the new UI having Go to UI screen**\n",
    "\n",
    "*   Refer to this insruction in this <a href=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DB0201EN-SkillsNetwork/labs/Labs_Coursera_V5/labs/Lab%20-%20Sign%20up%20for%20IBM%20Cloud%20-%20Create%20Db2%20service%20instance%20-%20Get%20started%20with%20the%20Db2%20console/instructional-labs.md.html?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2022-01-01\">link</a> for viewing  the new  Go to UI screen.\n",
    "\n",
    "*   Later click on **Data link(below SQL)**  in the Go to UI screen  and click on **Load Data** tab.\n",
    "\n",
    "*   Later browse for the downloaded spacex file.\n",
    "\n",
    "<img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/labs/module_2/images/browsefile.png\" width=\"800\"/>\n",
    "\n",
    "*   Once done select the schema andload the file.\n",
    "\n",
    " <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/labs/module_2/images/spacexload3.png\" width=\"800\"/>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Building wheels for collected packages: ibm-db\n",
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      "  Building wheel for ibm-db (pyproject.toml): finished with status 'done'\n",
      "  Created wheel for ibm-db: filename=ibm_db-3.1.2-py3-none-any.whl size=29943462 sha256=8f17a4a08d8b0ae4d4c4603badf531fcfc2e14a4bb836d7a9d4dfb074c0a87c9\n",
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      "Successfully built ibm-db\n",
      "Installing collected packages: ibm-db, ibm_db_sa\n",
      "Successfully installed ibm-db-3.1.2 ibm_db_sa-0.3.8\n",
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      "Building wheels for collected packages: prettytable\n",
      "  Building wheel for prettytable (setup.py): started\n",
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      "  Created wheel for prettytable: filename=prettytable-0.7.2-py3-none-any.whl size=13704 sha256=db6f3fa9774b06c09ce4017696cc41ac10306b760db76acbc5fd9b1e0100ce55\n",
      "  Stored in directory: c:\\users\\betur\\appdata\\local\\pip\\cache\\wheels\\48\\6d\\77\\9517cb933af254f51a446f1a5ec9c2be3e45f17384940bce68\n",
      "Successfully built prettytable\n",
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      "Successfully installed ipython-sql-0.4.1 prettytable-0.7.2 sqlparse-0.4.2\n"
     ]
    }
   ],
   "source": [
    "!pip install sqlalchemy==1.3.9\n",
    "!pip install ibm_db_sa\n",
    "!pip install ipython-sql"
   ]
  },
  {
   "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": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext sql"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv, sqlite3\n",
    "\n",
    "con = sqlite3.connect(\"my_data1.db\")\n",
    "cur = con.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install -q pandas==1.1.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "%sql sqlite:///my_data1.db"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\betur\\anaconda3\\lib\\site-packages\\pandas\\core\\generic.py:2605: UserWarning: The spaces in these column names will not be changed. In pandas versions < 0.14, spaces were converted to underscores.\n",
      "  sql.to_sql(\n"
     ]
    }
   ],
   "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": "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",
    "##### Display the names of the unique launch sites  in the space mission\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///my_data1.db\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>Launch_Site</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>CCAFS LC-40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>VAFB SLC-4E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>KSC LC-39A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>CCAFS SLC-40</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[('CCAFS LC-40',), ('VAFB SLC-4E',), ('KSC LC-39A',), ('CCAFS SLC-40',)]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql select distinct(LAUNCH_SITE) from SPACEXTBL"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 2\n",
    "\n",
    "##### Display 5 records where launch sites begin with the string 'CCA'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///my_data1.db\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>Date</th>\n",
       "        <th>Time (UTC)</th>\n",
       "        <th>Booster_Version</th>\n",
       "        <th>Launch_Site</th>\n",
       "        <th>Payload</th>\n",
       "        <th>PAYLOAD_MASS__KG_</th>\n",
       "        <th>Orbit</th>\n",
       "        <th>Customer</th>\n",
       "        <th>Mission_Outcome</th>\n",
       "        <th>Landing _Outcome</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>04-06-2010</td>\n",
       "        <td>18:45:00</td>\n",
       "        <td>F9 v1.0  B0003</td>\n",
       "        <td>CCAFS LC-40</td>\n",
       "        <td>Dragon Spacecraft Qualification Unit</td>\n",
       "        <td>0</td>\n",
       "        <td>LEO</td>\n",
       "        <td>SpaceX</td>\n",
       "        <td>Success</td>\n",
       "        <td>Failure (parachute)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>08-12-2010</td>\n",
       "        <td>15:43:00</td>\n",
       "        <td>F9 v1.0  B0004</td>\n",
       "        <td>CCAFS LC-40</td>\n",
       "        <td>Dragon demo flight C1, two CubeSats, barrel of Brouere cheese</td>\n",
       "        <td>0</td>\n",
       "        <td>LEO (ISS)</td>\n",
       "        <td>NASA (COTS) NRO</td>\n",
       "        <td>Success</td>\n",
       "        <td>Failure (parachute)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>22-05-2012</td>\n",
       "        <td>07:44:00</td>\n",
       "        <td>F9 v1.0  B0005</td>\n",
       "        <td>CCAFS LC-40</td>\n",
       "        <td>Dragon demo flight C2</td>\n",
       "        <td>525</td>\n",
       "        <td>LEO (ISS)</td>\n",
       "        <td>NASA (COTS)</td>\n",
       "        <td>Success</td>\n",
       "        <td>No attempt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>08-10-2012</td>\n",
       "        <td>00:35:00</td>\n",
       "        <td>F9 v1.0  B0006</td>\n",
       "        <td>CCAFS LC-40</td>\n",
       "        <td>SpaceX CRS-1</td>\n",
       "        <td>500</td>\n",
       "        <td>LEO (ISS)</td>\n",
       "        <td>NASA (CRS)</td>\n",
       "        <td>Success</td>\n",
       "        <td>No attempt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>01-03-2013</td>\n",
       "        <td>15:10:00</td>\n",
       "        <td>F9 v1.0  B0007</td>\n",
       "        <td>CCAFS LC-40</td>\n",
       "        <td>SpaceX CRS-2</td>\n",
       "        <td>677</td>\n",
       "        <td>LEO (ISS)</td>\n",
       "        <td>NASA (CRS)</td>\n",
       "        <td>Success</td>\n",
       "        <td>No attempt</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[('04-06-2010', '18:45:00', 'F9 v1.0  B0003', 'CCAFS LC-40', 'Dragon Spacecraft Qualification Unit', 0, 'LEO', 'SpaceX', 'Success', 'Failure (parachute)'),\n",
       " ('08-12-2010', '15:43:00', 'F9 v1.0  B0004', 'CCAFS LC-40', 'Dragon demo flight C1, two CubeSats, barrel of Brouere cheese', 0, 'LEO (ISS)', 'NASA (COTS) NRO', 'Success', 'Failure (parachute)'),\n",
       " ('22-05-2012', '07:44:00', 'F9 v1.0  B0005', 'CCAFS LC-40', 'Dragon demo flight C2', 525, 'LEO (ISS)', 'NASA (COTS)', 'Success', 'No attempt'),\n",
       " ('08-10-2012', '00:35:00', 'F9 v1.0  B0006', 'CCAFS LC-40', 'SpaceX CRS-1', 500, 'LEO (ISS)', 'NASA (CRS)', 'Success', 'No attempt'),\n",
       " ('01-03-2013', '15:10:00', 'F9 v1.0  B0007', 'CCAFS LC-40', 'SpaceX CRS-2', 677, 'LEO (ISS)', 'NASA (CRS)', 'Success', 'No attempt')]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql select * from SPACEXTBL where LAUNCH_SITE like 'CCA%' limit 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 3\n",
    "\n",
    "##### Display the total payload mass carried by boosters launched by NASA (CRS)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///my_data1.db\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>sum(PAYLOAD_MASS__KG_)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>45596</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[(45596,)]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql select sum(PAYLOAD_MASS__KG_) from SPACEXTBL where CUSTOMER = 'NASA (CRS)'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 4\n",
    "\n",
    "##### Display average payload mass carried by booster version F9 v1.1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///my_data1.db\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>avg(PAYLOAD_MASS__KG_)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>2928.4</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[(2928.4,)]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql select avg(PAYLOAD_MASS__KG_) from SPACEXTBL 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",
    "*Hint:Use min function*\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///my_data1.db\n",
      "(sqlite3.OperationalError) no such column: Landing_Outcome\n",
      "[SQL: select min(DATE) 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) from SPACEXTBL 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": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///my_data1.db\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_ > 4000 and PAYLOAD_MASS__KG_ < 6000]\n",
      "(Background on this error at: http://sqlalche.me/e/e3q8)\n"
     ]
    }
   ],
   "source": [
    "%sql select BOOSTER_VERSION from SPACEXTBL where Landing_Outcome = 'Success (drone ship)' and PAYLOAD_MASS__KG_ > 4000 and PAYLOAD_MASS__KG_ < 6000"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 7\n",
    "\n",
    "##### List the total number of successful and failure mission outcomes\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///my_data1.db\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>count(MISSION_OUTCOME)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>99</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[(99,)]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql select count(MISSION_OUTCOME) from SPACEXTBL where MISSION_OUTCOME = 'Success' or MISSION_OUTCOME = 'Failure (in flight)'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 8\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": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///my_data1.db\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>Booster_Version</th>\n",
       "    </tr>\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",
       "</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": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql select BOOSTER_VERSION from SPACEXTBL where PAYLOAD_MASS__KG_ = (select max(PAYLOAD_MASS__KG_) from SPACEXTBL)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 9\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": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///my_data1.db\n",
      "(sqlite3.OperationalError) near \"select\": syntax error\n",
      "[SQL: SELECT EXTRACT(MONTH, select min(DATE) from SPACEXTBL where Landing__Outcome = 'Success (ground pad)' )]\n",
      "(Background on this error at: http://sqlalche.me/e/e3q8)\n"
     ]
    }
   ],
   "source": [
    "%sql SELECT EXTRACT(MONTH, select min(DATE) from SPACEXTBL where Landing__Outcome = 'Success (ground pad)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 10\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": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite:///my_data1.db\n",
      "(sqlite3.OperationalError) no such column: Landing__Outcome\n",
      "[SQL: select * from SPACEXTBL where Landing__Outcome like 'Success%' and (DATE between '2010-06-04' and '2017-03-20' ) order by date desc]\n",
      "(Background on this error at: http://sqlalche.me/e/e3q8)\n"
     ]
    }
   ],
   "source": [
    "%sql select * from SPACEXTBL where Landing__Outcome like 'Success%' and (DATE between '2010-06-04' and '2017-03-20') order by date 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?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2022-01-01&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?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2022-01-01&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?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2022-01-01&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?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2022-01-01\">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?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2022-01-01\">Hands-on Lab: Analyzing a real World Data Set</a>\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",
    "\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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