SQL/JOIN_basic.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SQL joining (merging) tables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Packages and database files needed for this project"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Note:* This section is repeated in several notebooks in order to make them functional as independent lectures."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import needed packages:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import urllib.request    # needed for download of the example database\n",
    "import shutil            # needed for unziping of the example database\n",
    "\n",
    "from sqlalchemy import * # package providing unified access to various databases"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If necessary, download the database:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import urllib.request    # needed for download of the example database\n",
    "import shutil            # needed for unziping of the example database\n",
    "import os                # for checking existence/removing of a file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not os.path.isfile(\"chinook.db\"):\n",
    "    urllib.request.urlretrieve(\"https://www.sqlitetutorial.net/wp-content/uploads/2018/03/chinook.zip\", \"chinook.zip\")\n",
    "    shutil.unpack_archive(\"chinook.zip\")\n",
    "    os.remove(\"chinook.zip\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this session we use the magic database connector. Install `ipython-sql` when necessary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install ipython-sql #In case the SQLite not working in Jupyter\n",
    "%load_ext sql\n",
    "%sql sqlite:///chinook.db"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `INNER JOIN` - all matching rows "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Overview"
   ]
  },
  {
   "attachments": {
    "inner_join.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Suppose you have two tables `A` and `B`:\n",
    "- `A` has columns `a1`, `a2`, and `f`. \n",
    "- `B` has columns `b1`, `b2`, and `f`.\n",
    "- The `A` table links to the `B` table using the foreign key `f`.\n",
    "\n",
    "The following diagram shows the values of `f` present in both tables.  \n",
    "Typically, the `INNER JOIN` operation matches and merges rows for the `f` values present in the both tables.\n",
    "\n",
    "![inner_join.png](attachment:inner_join.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`INNER JOIN` uses the following syntax:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```sql\n",
    "SELECT a1, a2, b1, b2\n",
    "  FROM A\n",
    "  INNER JOIN B ON B.f = A.f\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or, a simplified syntax when in both tables the name(s) of the column(s) to join on are the same (you may type many comma-separated column names after `f`):"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```sql\n",
    "SELECT a1, a2, b1, b2\n",
    "  FROM A\n",
    "  INNER JOIN B USING ( f )\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example (joining two tables)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let’s take a look at the `tracks` and albums `tables`. \n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "The `tracks` table links to the `albums` table via `AlbumId` column:\n",
    "- In the tracks table, the `AlbumId` column is a foreign key to the `albums` table. \n",
    "- In the `albums` table, the `AlbumId` is the primary key."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT *\n",
    "  FROM tracks\n",
    "  INNER JOIN albums ON albums.AlbumId = tracks.AlbumId\n",
    "  LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note above, that since the `AlbumId` column is present in both tables it is reported twice (and once the column name gets adjusted to avoid identical repetition).\n",
    "\n",
    "With the `USING` notation the `AlbumId` column is not unnecesarily repeated:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT *\n",
    "  FROM tracks\n",
    "  INNER JOIN albums USING ( AlbumId )\n",
    "  LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example (joining three tables with `AS`-renamed columns and renamed tables)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tables: `tracks`, `albums` and `artists` are related as follows:\n",
    "- One track belongs to zero/one album and one album have (m)any tracks. The `tracks` table associated with the `albums` table via `AlbumId` foreign key column.\n",
    "- One album belongs to exactly one artist and one artist has (m)any albums. The `albums` table links to the `artists` table via `ArtistId` foreign key column.\n",
    "\n",
    "![image.png](attachment:image.png)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT \n",
    "    tcs.TrackId,\n",
    "    tcs.Name AS Track,\n",
    "    als.Title AS Album,\n",
    "    ars.Name AS Artist\n",
    "  FROM tracks tcs\n",
    "  INNER JOIN albums als ON als.AlbumId = tcs.AlbumId\n",
    "  INNER JOIN artists ars ON ars.ArtistId = als.ArtistId\n",
    "  LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `LEFT JOIN` - all left rows with and without matches to the right rows"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `LEFT JOIN` operation returns each row from the left side table independently whether a matching row is found or not: \n",
    "- When a match if found then its columns are merged in the result, separately for each matching row of the right table.\n",
    "- When no match is found the columns corresponding to the right table are filled with `NULL`."
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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dSNfV1eGAENbB0pYWVAnYjEumqQ3awmke7z/Q+I0ZtXQHjQpWoAgazluwKSipkc54O3t0p1H48F08MdwNSuoSgio2m5EWmCBoJvzxXbcOdtEfg2XRDzc/MLeuTVAbX2nAc7/+2eiMzEzbzbPtopMGBX6aCg3GUksCqnhsVtE3XJGsSNL08H7w8LC+Z3czjjuxSyjjkQWblq+oN0obAmrZi/Vw2hDWJfRnRsmT7dbU1MBpY5Cr+KCKxGaeYDoKBlo6TDORyDcOSGbBkp+Frx0/dY3ByyigcskSBBh61JVAh2H/XAKymKAKzmZA4o+D6oKQBS7ZUWkBHYnBBdVFLFBZHwYaaMwVZaaHQSZLdrO6raKBKiyboTKBVUNU4b1eqB596ecjTQOypJJkMaDyyPErDPmbGNT9c+qefGazvD5pCG3bMJtRwvDd6dOnB6OuRQDVkZHk8JIl/pU+L1Tetm2bvALj0uufH+eoSgYIgyNQ+Vc79qUF6srh/fr26Ua4o7GxSV+TTiGOYOTIkfqIWwlKXllZSbjj8OHDuuRFAFUo3xxscYhVIS3cVcnUSlAbpAUKf48EN0J4xVScmnMpJngg6SwZIbyCgioIm4NhOGodl+yuuqCOg2G41EFNva/WCI+UJM6VIqG51JQpU9AY8pqFA5U+m4OlR10sfvQqd9UFNRHkWYFA8cwwziLjJMS5cG/u9guxHt4NQSsjWgUClTKbg1Smm89cC/loOpcOUrmgoJQ094zQqhNVaEKnyeZgT/b7Dw+7+7bBztFXFjgYcygCKAZlbp66RoZNcGaEhhwdL1T2ZPgMGS0DXKmDSo3NjAYh8CUPUBdO9/nAwrgdsy9KAioYB0RuIjkcHVtRNgxGbNMFlc6M0HYqS8ankmZciX7zJWJxLl6NiCeESOX6JbkIjyIPJAzWd08XVApsDlKZttg/r1x8UIrQjMsUqO71ZYuZUIRmgr++aYqEzpfNQSrTQ3JdKwcFRqlAQWjGTQkFFqLu9TWLnIDQjKQgmvV90yJ0XrqZjqpsNShcQTv7GnxBE4QUhlyzXN6i5KCCUQ66UytXrpSFdC4djHLkDyq5b1alkUYsea3LwiRLK97Ic20AxagTGlp6aHwbwVBZTufSRNDR0NJD5w8qIZvVoKUMH9pQ63nWKGEE4mIy0GsPqCChGWBjVCJPyKU9PUjoPEElVBqDBw9G62hb0PXetG6C3nU0UTVquQzxWgiKdYdM55DmxZ85uhBLo2CFKBpD75JIDCqJb6aNM6hMOyhL42KaAT+DyhaC4p04RPGleYnxI/nkEefSPI3GRI7EoGKzmSCGvDdijk63o5PudcUTxJDTfWwGRegT/aNLjtij7p0OQoOFydxy6C0xqHhsxg0Yq0ierx7t9HQiTEnPj4V6mh8kLAfFvBfmPOkC004alaJ/ciixZMkSxoZ0gZOBisdmHiDZ82OhtbWv0tJ2aTMxdUat7Pk5AYrnTYY4aC1Rn20itTwDclmGOBKAisFmJhVJucyy5JnTqyw3UJvFY1KRlMuugELaQWiJDkfDtB55xLm0GlWRxY4LKupKKjSGVDYMt66qub683O2PAKEx5KQit0ApgaeXq7BmiRdHjR8/XrLBuTQj3plMhji0KnlcUFHZPGTIEKkxcAwXntfDOWMZBR5+/QtSYzgHCpkHm/WLwliCyWo8Y3TWgGz/LuqZZXj6lW6xQEVSGnPmzNFXxxy8lMgDufzI/E2aB+6CImAnBTTdQdfjG9QFilkK6Oig2vbNapK1fqZpjlc/e73edTTBdHg5DOEuKAT0GT1P1u+/o2nevXu3MRjhXB1B5V69etEpVCWPDqpt3yzlMlc3ovfOWUoVWMpl10ERgZYBOxwbLbWj9aKLTQRaBuwigmqDzcR9tCTnTn5oDMaHdefJD1BBvaFp4W4iqDfaxNKG0hg1apTu/KHP6Ce5HsfAImMnrdKdPz9AoTcONzbpRxSx4UF3EL3R2NionWkUUGG+mUFs2fljWMH1EWyozCC27Pz5AQpcNJuof+29CvcKK32LIiTo/8lVKm2CCmOzPJkJZa6vKFHW5wW1uhq8AQUiHA2vktLQcEM4I73raILxFPk+uzZB5WSz4ZilpRw1DcU2HLMfoHR1MMNOdgelM9J5nEsww052B8NB5WSzPA0beRBgpiKlY/YGlCQowknvtunJdE7LE5KK4aCys9lwzGgyywFHKZ7hmP0AZQDH6SCf9EHJA33QuQTfU5QDnCGgsrNZnoB1LPlwap7VIB2zN6CCNuFzBfpguCfT2exPSEKGgMrCZjlKDk5pHfth5yohL6uVoQw/QGUFi+uR7pmobdZsbh1EPUv3nAtUFjbLXiRBHz8cs3x/vTegcjHybqEMide6vtRKwZQrEnKBMtnMrAw9Ps5V/BCXzMrQMxm8AZWLyhxnrFtORZLuKeQsy39irFtORcoKymSzHnpR2PimquUgoxRPD5L5BCocuKw4o07DT7T5VzllKCsok82S8izE8GDwj+pZJD6T4w2ocNpJNtNt8mCdFXglm7OCOo7NyAy5VkpaJNx2Nv+KzJBrpfwA1abBeZuM7AtK9djmudZm4G0ysi8YBHUcm+XPCC8/+n9rxLevvQEVhXDyuZU1G+Vca/NI9xwElZPNtMjWQopVMNn/8wZUFAuMFjXIREgPJj2DWi5ECII6xmZW4EhlLW0RxXZ25uHVcrIL6AeoiKZmGax/YoNvZYSIjWNsNvy2HzJDOmZI4AeoiGxuxSvcs1G/0S9iW07png1Qx9gsHbM3LfLGTQ26MrwBpRG1mZBsJgjg+gs3FF7JZgNUdjZLK7RpMpsznLAyQ1UKkQ05hV86LJtrLbxsRDbkFH4J6iibeWqhub7KpWIelj7oXILYnJyb4QeouLUgUcuKj3sdq/JL6SxBHWWzDDPzNPNMW1X6ZIXZWr9Hn+gNKI0oYkI2s7KWI55uZzYpNiSoLGyWT7OdYCKWSrLZG1ARsetsEriseJ3BxYT0zRLUUTZLdy3xuwhVl1mKZm9AaXQRE0Yz60fUGeks4WtQWXyzXFsmz3EuLX2zN6AS1ILELj1ZgkvZc4pcLKhBtbKZcRP90gx2/XBjjJvol2Z4AyoZmWSFyr5+sqtZcpYUGxpUK5s1tUkzk8GPeXPSMXsDKhmTZJBO1nWyq1lylgzSaVCtbNbUJi2fY0vKnawY7bE5bTdZp7KudQYXEzl9s0Qon2MXQeoy72o4qNPegNKIYiX6incgybqOdRHbMkvfrEGZSkMitw1ArPJIpeENqFgW0JmNzyzpdllncDHB9CNZbLX2sZXN/nUBAdXeBZSVLVsnWd0yj3Np6Z4VqFY2y40Ok9z1I+0lqFhV42XrJNmsrNHKZjl0EstGNmeWQyc2l7P4ZfOyuhUo0zf78b45gyJegjIwhu/KAZTwnA79KgdQVLFNNjsEpr2o7RYwLNDOZsMg7bsOW6CdzQ5XXnvRDQt00POPjB+c3uUdik6Xv6CF9yPebJhIgWr3zYZZ/N/1Jt4sq+povFmOd8ufnU7LmQlOAylE4b2scQWqAx9KKYTJSntNP6YBFsiG8k2bBbpF8S+rQLUrjeJb3uU7/u7df7r7SxdUntP7DLYep/a+4sGffNBsDaBO1pSkvSAOWKDl4Paf//NbZ419aOKgigzl7VQx4I+6tybs2NrZbEc9OFKKlk8+3tdYPnDUxCmjelrYrLcWSQopb2JbcqaRN6ASc17OWpHVHfeCsPk3R8r2129Ysfy5VRve3NPYEvcKKeaXE06O6WaLOrnNjdtffnX65JrLblo/b+3efXkosvzDGk173p11y5qn3zgSrcZaPt37wYq/qx07quZP7vhp9YZ9B/IofIpVHrxUHtXd8nHD22/se79mxk03T5xw/YiqP/3msrcORTNPsBypHjka00j1mnlerOmdtXU33bNt/yUDbx/aofavaxf94pMSmarlyMf7a2v+4+mNO/61/uMotGz57Z5/vO9Hk144dN51A2846/8WT1v31H8dLlHh86yFkNMzp1x07YN/u+jFf9954PDH7214qN/aBx5/6ddR7BNy0RR/MnUzSzZKNuPsyN61i+t7TfvqotvPOLl5X9fXah59df+3q/6gPG+4cUEdeeet26bU/vjd1hsfaWqJQMqW/ZvffrK+/xPLRt56YedM87mVB56Z+8pv7r2sd9e8C5/KBeRKnHwu2PH0gaNuPL/HOT27ZMq6XTFp6g0L7vrF2x+NPeuzLmE+F05ybnBQs1U3y6ZHLtlIcoc8zmlp7ljRt9+VX+zetaylseHDn79RdslZXTsnvaBUGnFBdep5+le/de26dWNmXVTWFKkAmVMu6D/ne1U3XNA5U9a89/V3VtWV9TntpMSFj3TPOJmkBWR1x7lGa96m7T+a9McTF7/2W57wlk8+eO9/D5/atYvpEeNeNGl+OaipQLWWRHYL5OLQpHdJeF6my2l/sWhMWYey3+399RMPr1vTb8iK4d06JrxY66sU9KlxQWVOPW3UmNPKmj58vaysuTlSQ9r59N7jrm69YdPObd/8+oZ/Kbvo2WE9LGEzb5fUpiAhq1sej5LuUPnl8V+e+Z1v/9WRcf13r1v09OY/e3ze4K6lCNEZb+9Vg4CtvlmuSJEL96PASzdPpkPZpx+89/iMFx99/+LH5n3h8jwaMLl2KDGolmieWRqhw+dOG3t9/wGHti18rmFvpAdBnl2QtHyYjcWhce+X6XLhhAUvzr5kxzPzlr7Ve+rStX9/6+dLQuYyvU4bCJrArb5Z75CWyONCzTt/S+P7u/7mW6ueOnjxwieH3XQurXbyTa7rTAyqVTFHKkTL4YaG9Q3dRlZVlHc7/WsPXvOli/9t+Lydm79+9pV/GOn85DgjnCkf5srKyghnhGTJdDl76J3zh97xeEsmU0poWdls6maJPARTIX5qObT32dmrnjoyuPqpYTeflxeVKZ7UzUlBtaAyOtNeRNg+fHXr9Ae2/mzfZz3G5uaPDjaWdT2p3A6pIR/mfESzNENpqUxJJJs1qFbfbEw8YqyhFGGNlk9/tat6fdllt1d89Mvty36Z6dy5Y3n5Sb0v7nPZWUmYbUw8SgKquaypqeykTlFcUKbPZRde07R2xn3Nt1xR0bR9R/Vz71V9r+oLp5TSe2nypTV0oi9oQyI4dEKpjjoeuWAwrWhOTMyZk84/9ztTz/7vFRse+v4rTzz7evWSTd+dtXH+xgONMS+ks8ulnUlAdSg/b2j/L/Ytj+KcO/Q6d271tbf02vfjxf+5dm+PexZPWPS1nifropQ0IbHLii5pofK9uQzPaVBHoyv4ak12CT7fe8Y5P9O1x1dm3vCVmXHOCc2L2NBuKQmojhXXfXf0daG3ED92+NyA8+97hD9xzIIkAY20wnMWoDlaBAIawfAcvx31O1p5cChJxdsDVJRESmdvQAl8kZISON19Q1VGuoR9maRjlqCysJmvUvPyY/sgxC6RZLM3oOJaQbdOnCh9VtzrWJVf6wgD1FE2G6/elyawCkaswhgfSfADVCwLkFl+MfFEYTOwtZQm7U3Fy46gN6CiE5o2lkZJ55dVrA86l+BTEFJpSFDH+uvyqHygnUMrCyzZ7A0oCTA8bTzAw4YNC8/vxK9SZlBgCeoYm+U32HigjcF9J3AGCym/lucNqCDMXEfW1O7QP8n61QddTMhvaxugjrEZ6Szno0hDuIhZlRnpLKcf+QEqenWsPWHZjI0k05etqI9uNZtzyo/FewMqisHXvLRDRpqlkoxyup15Vq9eLSPNBqhjvpnSSzZ70y6fsGJDNkREM/KcPWcJuaXMCII6js1jxozxT2yMvrr/iSk2pMyYPHmyJXTMsxiSzUFQx7GZO0n3/OQzm/O8tyWnS7HhDahw2y57sV7KDFmt4Sfa/GtNTY2UGUFQJpsl35lIufXNY9FKm3GGl23iuAE6gzegNKKsCSkzEJf+yYysoEw2E71j4FsbaJEX7pkJrnLyvh+gdB0FE0RX/ZMZzDQKlxnYwWQzh6R7Xr6i3o85G9I9ewMqyGN1RKopOkLBFjnXiTYfX7BggS5eLlBtsJnzpWn05ZxLSDZ7AyprLeB9ZCASKnswb47R7KVLl2q8uUBlYTMaSz7NsNkD98z3TI2+oAegdO3KBPUl+3/Tpk2TvzqaxjHL/l8uUFnYDGCZG9P44Z7vunWwrktvQGlEKsEjKiuLrpIxO9LI78QujlnKjBBQ2dlMX5BzNFQ/3DN9QTkJyQ9Quo5UAlDSMc+ePdvI4OKu4ZhDQGVnM5jlOd54sgenVenq9AaURhR0zHJ+mc7mViLomENA5WRzu3t2q9Yp7QnumLFATjbzm+Ge759b51wFBwtsuGc/QAGTGPO8BZs0XoRiiA/T2SxPEGOWJGwTVBibMYcMbhCm9WDSM+pZBjf8AAUpHxFUZld2myynbEjxJJWjgApjc/D8b8yoDbm3Kz/94OHjlmB4AIp33/BYavsz/uVBKIPvssoYcxRQHQ36a4uoBIMueHu9DItJDryt0Fg9apxi/y6vQeJlVnrBnAegRo5fIUMZjABTcfZXRHgJR4wYIWPMUUC14Zu5H22WNA1C0wO9gXuW00SdBnX/nDoeSM0M3JMHc4ymT58u3zQXEVSmJcKr45mJJydvoDtf+IfR2nyOJpgzKTWGo6CY5DjkmuW6CpgxtnPnTr3raGLLli3yZQnRQbXtm7HIpEmT5GAK87MW/dD5qc8TbxwgB1NcBEWA+eapayRlpdCUxx1KE2CWsQdKHh1UJDarK0q98cDcOg+mPi9+9CqpN5wDRdsiNQbzETyIyqECpMaIBSoqm5FiRtBn6oxa1yfuMBXJiG84BAqlJCcx0xzPnz/fIR+ctahoWjmJOS6oNmIa8pZIGQTNtm3b1MEP9xz6YM8hVt3JPM6lic/w3sHtO/a5BYqGcdI96xobj33JgnemnHnmmc7ZXxYYdo0fP/7w4cP6YFxQUX2zugEKhsdF34wYpwcCGr0hV6bYD0rJZRmSo9l0PcCs5LIMySUAFSmmoelLwuhvcuT56tGue2gjMmA5qKpRy3WwnKLSZ1q5ciUJp7fBgwfrYQ2AJAMVzzdzG3yA0cekL+J6jxC9gYeWbLAW1NT7aiWVkX9GdUgUrqSnTJkiqZwYVGw2YyACdjL8TJPHWJTrPUICdhPE0m47QT0yf5McwSbKBJVdXyg1Z84c+UDmAyq20tCPu9E0XDKg5/rnxxnfztGZXUkYjbhVoIzhHkxK958X+rhi26zlNAbm8gSVxDerYtHflAM2NH8eeGgeSBis7W4PqCCV8Wf+UTlPUMnZTAPHveWQCnWP3HRactC2VB8/pGIDKN6PaMzDRumh9/RT52KC9yPK5adAyB9UcqWhLEiIg0FvGVhhuJgoh9OSg06tMSuthKCg8vjjh6+p9SVLlrjIYF1mqGwMX6cCKl82U74goRkupsl2euJokNAlAUUEQ3b7sHYqta5ZVZIEEQzZ7UsRVApspjTBR60kdZ9u3QSdYpFBBalMM0jPz+kgRpDKKYJKrpsldeiOGJOpVYTL6Tg0Q0JIJhiskRYTVJDKNM3+UTldUOn4ZlXfDE7ynMkweJGdmaZdigk6tWho+oL6mkUAFaQyTbPr3b6gV04dVDq+WdU0LaARtsOZMZecmL+mgnMJurNG2K6goGjNiHkbWjn1Wi9yLdCzYnTC0MqFAJWmb1Y2CnpojjPMVv3YcUPHRTZonrcLeuhCgAp2PblLIWo9T2vEOj0YJCgcqDR9swKpPDRdb4kZZzPyZodHv5WHlkPfoEsXFOMjRliQWD5tndMCg6E+I4BbUFAx5jdLdoany8vLUfeZTIbK0DlZJbFizXaWfF94Xg990KFEeXknNVVQflIyFVA4/r+c+TLvdpHzlRlnpc93+eWXO2QiWVSa6DvvvJPVqXK+cqFBFYTNChUPZWVlJVWiQaI4ITS7vKJFH3QrQcl5IOWijzxBoS5Y2/eTul3SDtQ6jsDdpdeoC9zZ+vXriwyqgGwGCbWC/Ge5yu7duzUwfBt/lw7oecbpJ+uDDiUYFaLwb+/Yx+obXexkoOgf3zvzZbm2jwsy3otWdjeozJy4O+64Q67tKxqo9HuBuoJ1Qi0rkKqDn4hzsSaPeZg6m1sJ5AEDzlJ1xAKV9XQ0JQsu3BXKWSu6mKCKwWZFU973gcuRMzo4zoQ1Zvm4OwbOm1n4LANiQz6KbYLCJcs3IKpzacewj7sLonDJwfdmFRlU8dhMnSk5ZbRBHOfNLCz9cHSikhK+hlrIBYrRcqYZGuwnM+rC3RXXzGsghGX4qZKAKiqbQUhjRGMafIgRHnzJYeb0KvI4tyEbeHdy0N1KUJCeWZ2GMgEp3guDOPoeDNwTz6GhIUsIqthsVkzl9Y9YQY6Bq+OsnYbTd9927AMl6rgT/3lRJ3yVY+AaFGGQII8RlLg0HmwXO3y8a5MalAErBba0oErDZoV84cKFWCTIVNVBRH64qD14JQPvTAqCMo7gkqGCizE4/DFPYJDHACw5qFKyGfwID/xTVtPAaQhN3MM5TiM8jIlKBpXp7bkYuEAfw+Ngiwo6XDKgSr6yq8RsVtWcq9lSvzKePLSqjxOxPN4FTIiDv2Cn0CA0zzCjS05wmtqBqWzB7jugeFsQDey9995rACzJrhVsVshpwugPYbWshsBV8z1W/iwM5+GMGR2ExEFxnBWLPqhUJsy2MDBHs0mbSXUEO3mq/FbxWBXJIjarAilOY8dgxEdloKfIKj1oXfLhcTwx9A0nMVIS10XFQ4sQUGTAVUPrkgc38MTQN4TE1IICxdi1bf1X69isKItjwKC46qytm8rDf2it/hhqLo68JtDGWxg3fjY4Hy4noKbBzoigoLXaIE1x6IIHQQ1DYrZwgwdB6bqwIWEpm7Vp1KdcYLY+kivBCBycJhYGv/nP22xz5Yx1nLgbrOU7KbhheBwc+DCuptpfaj2EiNFBQWg25bn5n1YMhALAWjboC49zNYMaWhRQOnMJE7azWZlGeTVMnzX6kct88Lt7ty4IblieK0/wOHyFtRyPwl19OvVNy8sWXSokAwW5UdtsJPTd20zAVxWLiMJdfbUEoPS5JUm4wWZpGiaAQ2s2XIs8XpK0kgR44jy9ppegil8j7rFZ20j1V6A1/oZNHy9oQjlFReLobjh6kbwEFR1+njkdZrNETqsNoWG2alJbJWFKnhviKgbT7NK4FzOU5iUoWWuppz1hc1a70FWH3AmYDYO5INwN6cllvWMRDnoJKi27+czmtGzUfh1XLPD/ZghhWTuipDQAAAAASUVORK5CYII="
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Summarizing:\n",
    "- You will use `INNER JOIN` when you want to return only records having pair on both sides\n",
    "- You will use `LEFT JOIN` when you need all records from the left table, no matter if they have pair in the right table or not."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example (trial)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT ArtistId, Name, COUNT(AlbumId) AS AlbumsNum FROM artists\n",
    "  LEFT JOIN albums USING (ArtistId)\n",
    "  GROUP BY ArtistId\n",
    "  ORDER BY AlbumsNum"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example (joining to count)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's consider the goal of counting the number of albums for each artist.  \n",
    "Note, that there might be some artists with no albums and the count for them should be zero.\n",
    "\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's start by `LEFT JOIN` of `artists` and `albums`.  \n",
    "Then, all artists should be there, possibly with `NULL` albums."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT *\n",
    "  FROM artists\n",
    "  LEFT JOIN albums USING (ArtistId)\n",
    "  LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's add counting when `GROUP`ped `BY` `ArtistId`.  \n",
    "*Note:* the `COUNT` is done for the `AlbumId` column, so `NULL` entries possibly obtained from `LEFT JOIN` give proper zero counts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT ArtistId, Name, COUNT(AlbumId)\n",
    "  FROM artists\n",
    "  LEFT JOIN albums USING (ArtistId)\n",
    "  GROUP BY ArtistId\n",
    "  LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's rename the columns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT ArtistId, Name AS ArtistName, COUNT(AlbumId) AS AlbumsNum\n",
    "  FROM artists\n",
    "  LEFT JOIN albums USING (ArtistId)\n",
    "  GROUP BY ArtistId\n",
    "  LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example - `CREATE TEMP TABLE` stores a table temporarily"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Modify the last code with an extra line(s) at the top and remove the `LIMIT` part:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "DROP TABLE IF EXISTS counttab; --- not really needed, only for multiple execution\n",
    "CREATE TEMP TABLE counttab AS\n",
    "    SELECT ArtistId, Name AS ArtistName, COUNT(AlbumId) AS AlbumsNum\n",
    "      FROM artists\n",
    "      LEFT JOIN albums USING (ArtistId)\n",
    "      GROUP BY ArtistId"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, the resulting table is stored as a new (temporary) table `counttab`.\n",
    "\n",
    "It is easy now to demonstrate some smallest counts (artists with zero counts are there):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%sql SELECT * FROM counttab ORDER BY AlbumsNum ASC LIMIT 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%sql SELECT * FROM counttab ORDER BY AlbumsNum DESC LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `RIGHT JOIN` - all right rows with and without matches to the left rows"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`RIGHT JOIN` is equivalent to the `LEFT JOIN` with swapped left and right tables.\n",
    "\n",
    "`RIGHT JOIN` is currently not supported by SQLite, so no example here."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `FULL OUTER JOIN` - all matching rows paired and all non-matching with `NULL`s"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The result set of the full outer join has `NULL` values for every column of the table that does not have a matching row in the other table. For the all pairs of matching rows, the `FULL OUTER JOIN` produces a single row with values from columns of the rows in both tables.\n",
    "\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`FULL OUTER JOIN` is currently not supported by SQLLite, so no example here.\n",
    "\n",
    "The outcome of `FULL OUTER JOIN` might be obtained by using `UNION ALL`. See [the SQLite tutorial](https://www.sqlitetutorial.net/sqlite-full-outer-join/) for details."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:sqlcourse]",
   "language": "python",
   "name": "conda-env-sqlcourse-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.1"
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 },
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}