jupyter-labs-eda-sql-coursera.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center>\n",
    "    <img src=\"https://gitlab.com/ibm/skills-network/courses/placeholder101/-/raw/master/labs/module%201/images/IDSNlogo.png\"  width=\"300\" alt=\"cognitiveclass.ai logo\"  />\n",
    "</center>\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-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2021-01-01\" 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",
    "    Here you should place the cursor at Date field and manually type as DD-MM-YYYY.\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-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2021-01-01\">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": [
      "Collecting sqlalchemy==1.3.9\n",
      "  Downloading SQLAlchemy-1.3.9.tar.gz (6.0 MB)\n",
      "\u001b[K     |████████████████████████████████| 6.0 MB 3.8 MB/s eta 0:00:01\n",
      "\u001b[?25hBuilding wheels for collected packages: sqlalchemy\n",
      "  Building wheel for sqlalchemy (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for sqlalchemy: filename=SQLAlchemy-1.3.9-cp38-cp38-linux_x86_64.whl size=1206995 sha256=aa854837871d0f2f72bb8019197c70c18c8531ed302424b656424e73a179014d\n",
      "  Stored in directory: /home/arindam/.cache/pip/wheels/cb/43/46/fa638f2422554332b7865d600275b24568bf60e76104a94bb4\n",
      "Successfully built sqlalchemy\n",
      "Installing collected packages: sqlalchemy\n",
      "  Attempting uninstall: sqlalchemy\n",
      "    Found existing installation: SQLAlchemy 1.3.18\n",
      "    Uninstalling SQLAlchemy-1.3.18:\n",
      "      Successfully uninstalled SQLAlchemy-1.3.18\n",
      "Successfully installed sqlalchemy-1.3.9\n",
      "Collecting ibm_db_sa\n",
      "  Downloading ibm_db_sa-0.3.7.tar.gz (30 kB)\n",
      "Requirement already satisfied: sqlalchemy>=0.7.3 in /home/arindam/anaconda3/lib/python3.8/site-packages (from ibm_db_sa) (1.3.9)\n",
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      "\u001b[K     |████████████████████████████████| 1.1 MB 4.1 MB/s eta 0:00:01\n",
      "\u001b[?25h  Installing build dependencies ... \u001b[?25ldone\n",
      "\u001b[?25h  Getting requirements to build wheel ... \u001b[?25ldone\n",
      "\u001b[?25h  Installing backend dependencies ... \u001b[?25ldone\n",
      "\u001b[?25h    Preparing wheel metadata ... \u001b[?25ldone\n",
      "\u001b[?25hBuilding wheels for collected packages: ibm-db-sa, ibm-db\n",
      "  Building wheel for ibm-db-sa (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for ibm-db-sa: filename=ibm_db_sa-0.3.7-py3-none-any.whl size=29303 sha256=08e82adc4a2c8359d412cd50d83de83ac6ba6eee01bb255e09e345b982c6a6bd\n",
      "  Stored in directory: /home/arindam/.cache/pip/wheels/56/a8/bf/19bbcc1d370b4fdc46c95228b6db3cdb5689b4afad12da3bc4\n",
      "  Building wheel for ibm-db (PEP 517) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for ibm-db: filename=ibm_db-3.1.1-cp38-cp38-linux_x86_64.whl size=41113130 sha256=26ccfb05e1cd0fae55c5b6f7760d03077a7ef82f2e0bbb61758462ef3b4f298e\n",
      "  Stored in directory: /home/arindam/.cache/pip/wheels/79/ca/5a/0aa8ee4ff812a4d3b02f09150732219e5fccbf03a84005b99c\n",
      "Successfully built ibm-db-sa ibm-db\n",
      "Installing collected packages: ibm-db, ibm-db-sa\n",
      "Successfully installed ibm-db-3.1.1 ibm-db-sa-0.3.7\n",
      "Collecting ipython-sql\n",
      "  Downloading ipython_sql-0.4.0-py3-none-any.whl (19 kB)\n",
      "Collecting sqlparse\n",
      "  Downloading sqlparse-0.4.2-py3-none-any.whl (42 kB)\n",
      "\u001b[K     |████████████████████████████████| 42 kB 916 kB/s eta 0:00:011\n",
      "\u001b[?25hRequirement already satisfied: sqlalchemy>=0.6.7 in /home/arindam/anaconda3/lib/python3.8/site-packages (from ipython-sql) (1.3.9)\n",
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      "Collecting prettytable<1\n",
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      "Requirement already satisfied: ptyprocess>=0.5 in /home/arindam/anaconda3/lib/python3.8/site-packages (from pexpect; sys_platform != \"win32\"->ipython>=1.0->ipython-sql) (0.6.0)\n",
      "Requirement already satisfied: wcwidth in /home/arindam/anaconda3/lib/python3.8/site-packages (from prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0->ipython>=1.0->ipython-sql) (0.2.5)\n",
      "Building wheels for collected packages: prettytable\n",
      "  Building wheel for prettytable (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for prettytable: filename=prettytable-0.7.2-py3-none-any.whl size=13698 sha256=05e2a5b8c12ba80c7544d711be2249291f16619325fb9c7d7d4deb2c7c5369f7\n",
      "  Stored in directory: /home/arindam/.cache/pip/wheels/46/60/6c/bb25d05df22906786206e901e9354bb3061061191116768bee\n",
      "Successfully built prettytable\n",
      "Installing collected packages: sqlparse, prettytable, ipython-sql\n",
      "Successfully installed ipython-sql-0.4.0 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": "markdown",
   "metadata": {},
   "source": [
    "**DB2 magic in case of old UI service credentials.**\n",
    "\n",
    "In the next cell enter your db2 connection string. Recall you created Service Credentials for your Db2 instance before. From the **uri** field of your Db2 service credentials copy everything after db2:// (except the double quote at the end) and paste it in the cell below after ibm_db_sa://\n",
    "\n",
    "<img src =\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DB0201EN-SkillsNetwork/labs/FinalModule_edX/images/URI.jpg\">\n",
    "\n",
    "in the following format\n",
    "\n",
    "**%sql ibm_db_sa://my-username:my-password\\@my-hostname:my-port/my-db-name**\n",
    "\n",
    "**DB2 magic in case of new UI service credentials.**\n",
    "\n",
    "<img src =\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/labs/module_2/images/servicecredentials.png\" width=600>  \n",
    "\n",
    "*   Use the following format.\n",
    "\n",
    "*   Add security=SSL at the end\n",
    "\n",
    "**%sql ibm_db_sa://my-username:my-password\\@my-hostname:my-port/my-db-name?security=SSL**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "%sql ibm_db_sa://vkl99601:QLHVk0OjS56nXpS6@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb?security=SSL"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tasks\n",
    "\n",
    "Now write and execute SQL queries to solve the assignment tasks.\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": [
      " * ibm_db_sa://vkl99601:***@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb\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>2010-06-04</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>2010-12-08</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>2012-05-22</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>2012-10-08</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>2013-03-01</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": [
       "[(datetime.date(2010, 6, 4), datetime.time(18, 45), 'F9 v1.0  B0003', 'CCAFS LC-40', 'Dragon Spacecraft Qualification Unit', 0, 'LEO', 'SpaceX', 'Success', 'Failure (parachute)'),\n",
       " (datetime.date(2010, 12, 8), datetime.time(15, 43), '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",
       " (datetime.date(2012, 5, 22), datetime.time(7, 44), 'F9 v1.0  B0005', 'CCAFS LC-40', 'Dragon demo flight C2', 525, 'LEO (ISS)', 'NASA (COTS)', 'Success', 'No attempt'),\n",
       " (datetime.date(2012, 10, 8), datetime.time(0, 35), 'F9 v1.0  B0006', 'CCAFS LC-40', 'SpaceX CRS-1', 500, 'LEO (ISS)', 'NASA (CRS)', 'Success', 'No attempt'),\n",
       " (datetime.date(2013, 3, 1), datetime.time(15, 10), 'F9 v1.0  B0007', 'CCAFS LC-40', 'SpaceX CRS-2', 677, 'LEO (ISS)', 'NASA (CRS)', 'Success', 'No attempt')]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql select * from SPACEXTBL limit 5;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * ibm_db_sa://vkl99601:***@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb\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>CCAFS SLC-40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>KSC LC-39A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>VAFB SLC-4E</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[('CCAFS LC-40',), ('CCAFS SLC-40',), ('KSC LC-39A',), ('VAFB SLC-4E',)]"
      ]
     },
     "execution_count": 8,
     "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": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * ibm_db_sa://vkl99601:***@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb\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>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",
       "</table>"
      ],
      "text/plain": [
       "[('CCAFS LC-40',),\n",
       " ('CCAFS LC-40',),\n",
       " ('CCAFS LC-40',),\n",
       " ('CCAFS LC-40',),\n",
       " ('CCAFS LC-40',)]"
      ]
     },
     "execution_count": 11,
     "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",
    "##### Display the total payload mass carried by boosters launched by NASA (CRS)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * ibm_db_sa://vkl99601:***@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>45596</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[(45596,)]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "select sum(payload_mass__kg_) from SPACEXTBL where customer = 'NASA (CRS)';"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%sql select distinct(customer) from SPACEXTBL;"
   ]
  },
  {
   "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": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * ibm_db_sa://vkl99601:***@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>2534</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[(2534,)]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "select avg(payload_mass__kg_) from SPACEXTBL where booster_version like 'F9 v1.1%';"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 5\n",
    "\n",
    "##### List the date when the first successful landing outcome in ground pad was acheived.\n",
    "\n",
    "*Hint:Use min function*\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * ibm_db_sa://vkl99601:***@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>DATE</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>2010-06-04</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[(datetime.date(2010, 6, 4),)]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql select DATE from SPACEXTBL where mission_outcome = 'Success' order by DATE limit 1;"
   ]
  },
  {
   "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": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * ibm_db_sa://vkl99601:***@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>booster_version</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>F9 FT  B1021.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>F9 FT  B1031.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>F9 FT B1022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>F9 FT B1026</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[('F9 FT  B1021.2',), ('F9 FT  B1031.2',), ('F9 FT B1022',), ('F9 FT B1026',)]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql select distinct(booster_version) from SPACEXTBL where landing__outcome = 'Success (drone ship)'  and payload_mass__kg_ between 4000 and 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": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * ibm_db_sa://vkl99601:***@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>61</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[(61,)]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql select count(*) from SPACEXTBL where landing__outcome like 'Success%';"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * ibm_db_sa://vkl99601:***@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>10</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[(10,)]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql select count(*) from SPACEXTBL where landing__outcome like 'Failure%';"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * ibm_db_sa://vkl99601:***@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>total_success</th>\n",
       "        <th>total_failure</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>61</td>\n",
       "        <td>10</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[(61, 10)]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT SUM(CASE WHEN landing__outcome like 'Success%' THEN 1 END) Total_Success\n",
    "      ,SUM(CASE WHEN landing__outcome like 'Failure%' THEN 1 END) Total_Failure\n",
    "from SPACEXTBL;\n"
   ]
  },
  {
   "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": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * ibm_db_sa://vkl99601:***@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb\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": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "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 failed landing_outcomes in drone ship, their booster versions, and launch site names for in year 2015\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * ibm_db_sa://vkl99601:***@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>landing__outcome</th>\n",
       "        <th>booster_version</th>\n",
       "        <th>launch_site</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>Failure (drone ship)</td>\n",
       "        <td>F9 v1.1 B1012</td>\n",
       "        <td>CCAFS LC-40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>Failure (drone ship)</td>\n",
       "        <td>F9 v1.1 B1015</td>\n",
       "        <td>CCAFS LC-40</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Failure (drone ship)', 'F9 v1.1 B1012', 'CCAFS LC-40'),\n",
       " ('Failure (drone ship)', 'F9 v1.1 B1015', 'CCAFS LC-40')]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "select landing__outcome, booster_version, launch_site from SPACEXTBL where DATE like '2015%' and landing__outcome = 'Failure (drone ship)';"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 10\n",
    "\n",
    "##### Rank the count of landing outcomes (such as Failure (drone ship) or Success (ground pad)) between the date 2010-06-04 and 2017-03-20, in descending order\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * ibm_db_sa://vkl99601:***@2f3279a5-73d1-4859-88f0-a6c3e6b4b907.c3n41cmd0nqnrk39u98g.databases.appdomain.cloud:30756/bludb\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>landing__outcome</th>\n",
       "        <th>cc</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>No attempt</td>\n",
       "        <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>Failure (drone ship)</td>\n",
       "        <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>Success (drone ship)</td>\n",
       "        <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>Controlled (ocean)</td>\n",
       "        <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>Success (ground pad)</td>\n",
       "        <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>Failure (parachute)</td>\n",
       "        <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>Uncontrolled (ocean)</td>\n",
       "        <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>Precluded (drone ship)</td>\n",
       "        <td>1</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[('No attempt', 10),\n",
       " ('Failure (drone ship)', 5),\n",
       " ('Success (drone ship)', 5),\n",
       " ('Controlled (ocean)', 3),\n",
       " ('Success (ground pad)', 3),\n",
       " ('Failure (parachute)', 2),\n",
       " ('Uncontrolled (ocean)', 2),\n",
       " ('Precluded (drone ship)', 1)]"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "select landing__outcome, count(*) cc from\n",
    "(select * from SPACEXTBL where DATE between '2010-06-04' and '2017-03-20')  group by landing__outcome  order by cc 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-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2021-01-01&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-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2021-01-01&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-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2021-01-01&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-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2021-01-01\">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-SkillsNetworkCoursesIBMDS0321ENSkillsNetwork26802033-2021-01-01\">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",
    "| 2021-10-12 | 0.4     | Lakshmi Holla | Changed markdown          |\n",
    "| 2021-08-24 | 0.3     | Lakshmi Holla | Added library update      |\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"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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