{
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"
    }
   },
   "cell_type": "markdown",
   "id": "7957b737-8742-49cb-84f6-9dee58df6b19",
   "metadata": {},
   "source": [
    "# Regression analysis with SQL \n",
    "![Screenshot 2023-03-27 at 12.00.27 AM.png](attachment:8a6629ef-d56e-4525-acf1-384e1914d994.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d2a03c2-9053-4425-b367-5bc5f594c8c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "import matplotlib.pyplot as plt\n",
    "from DATA225utils import make_connection, dataframe_query\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b743560b-2f67-4256-ba14-157600664bee",
   "metadata": {},
   "outputs": [],
   "source": [
    "conn = make_connection(config_file = 'StudentBooks.ini')\n",
    "cursor = conn.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c57cea5d-cfa2-4ce5-afcf-180b0d769f04",
   "metadata": {},
   "outputs": [],
   "source": [
    "cursor.execute('DROP TABLE IF EXISTS weights')\n",
    "\n",
    "sql = \"\"\"\n",
    "    CREATE TABLE weights\n",
    "    (\n",
    "        student DOUBLE NOT NULL,\n",
    "        books   DOUBLE NOT NULL,\n",
    "        PRIMARY KEY(student, books)\n",
    "    )\n",
    "    \"\"\"\n",
    "\n",
    "cursor.execute(sql)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5761ce74-2e15-4f9b-8759-8bc6ab7fd066",
   "metadata": {},
   "source": [
    "## Student and textbook weights with missing weights\n",
    "#### -1 is the placeholder for missing weights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "602b796a-5d5b-447d-b270-80d5728f7fb7",
   "metadata": {},
   "outputs": [],
   "source": [
    "student_weights  = [48.50, 54.50, 61.25, 65.00, 69.00, 74.50, 85.00,    -1, 89.00, 99.00, 105.00, 112.00, 123.00, 134.00, 142.00]\n",
    "textbook_weights = [ 8.00,  9.44, 10.08,    -1, 11.81, 12.28, 13.61, 14.00, 15.13, 15.47,     -1, 17.36,  18.07,  20.29,  16.06 ]\n",
    "\n",
    "values = list(zip(student_weights, textbook_weights))\n",
    "values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35552b93-0872-4ef5-842c-5b1c6ad3b209",
   "metadata": {},
   "source": [
    "## Load the `weights` table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a981909a-545d-483c-ac3b-326b5ce9ddbb",
   "metadata": {},
   "outputs": [],
   "source": [
    "sql = ( \"\"\"\n",
    "        INSERT INTO weights\n",
    "        VALUES (%s, %s)\n",
    "        \"\"\"\n",
    "      )\n",
    "\n",
    "cursor.executemany(sql, values)\n",
    "conn.commit()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3afffaef-579c-40cc-a520-a5ed1ccc2163",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Function to display the `weights` table and return its rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "875bcb8f-4a20-4c01-85b2-1fe0d8d4dec8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def display_and_return(cursor):\n",
    "    \"\"\"\n",
    "    Query the weights table, print its rows as a dataframe,\n",
    "    and return the rows as a numpy array.\n",
    "    \"\"\"\n",
    "    _, df = dataframe_query(conn, \"\"\"\n",
    "        SELECT student AS student_weights,\n",
    "               books AS book_weights\n",
    "        FROM weights\n",
    "        \"\"\"\n",
    "                           )\n",
    "    \n",
    "    display(df)\n",
    "    return df.to_numpy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88530e35-ade4-4a0b-b599-cbd19c4d3f6e",
   "metadata": {},
   "source": [
    "## The dirty `weights` table\n",
    "#### -1 is the placeholder for missing weights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8c9de453-6015-4c30-9614-567f58aa2eb2",
   "metadata": {},
   "outputs": [],
   "source": [
    "rows = display_and_return(cursor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee3f71fc-7256-4e04-9747-4d9b0b6097fa",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def draw_graph(max_x, m, b):\n",
    "    \"\"\"\n",
    "    Draw a linear regression trend line with slope m\n",
    "    and y intercept b from x = 0 to max_x.\n",
    "    \"\"\"\n",
    "    # The regression line. We only need the end points.\n",
    "    # End point 1: (0, b)\n",
    "    # End point 2: (max_x, m*max_x + b)\n",
    "    plt.plot([0, max_x], [b, max_x + b], color='red')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0562de3c-7bdd-4f02-b076-e1eb42ab14a5",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Function to execute multiple SQL statements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "74da08a1-ae19-4418-b884-786272dec6c0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def execute_multiple_SQL(cursor, sql, trace=False):\n",
    "    \"\"\"\n",
    "    Use the cursor to execute multiple SQL statements.\n",
    "    Print an execution trace if trace=True.\n",
    "    \"\"\"\n",
    "    for crsr in cursor.execute(sql, multi=True):\n",
    "        if crsr.with_rows:\n",
    "            results = crsr.fetchall()\n",
    "            if trace:\n",
    "                print(crsr.statement)\n",
    "                print('  ==> ', results)\n",
    "        else:\n",
    "            if trace:\n",
    "                print(crsr.statement)\n",
    "                if crsr.rowcount > 0:\n",
    "                    print(f'  ==> {crsr.rowcount} row(s) affected.')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0b28b13-b205-41fe-b517-a656482fd041",
   "metadata": {},
   "source": [
    "## SQL to clean the data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da314f6b-72b6-4425-9309-ae7dce2e56f3",
   "metadata": {},
   "source": [
    "#### In `SELECT` we must use the assignment operator `:=` because `=` is the equality operator."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "327d61c1-229c-4f5a-8280-a088b693353d",
   "metadata": {},
   "outputs": [],
   "source": [
    "sql = ( \n",
    "    \"\"\"\n",
    "    START TRANSACTION;\n",
    "\n",
    "    -- Compute slope m and the y intercept b.\n",
    "\n",
    "    SELECT @n      := COUNT(student),\n",
    "           @sum_x  := SUM(student), \n",
    "           @sum_y  := SUM(books), \n",
    "           @sum_xx := SUM(student*student), \n",
    "           @sum_xy := SUM(student*books),\n",
    "           @mean_x := AVG(student), \n",
    "           @mean_y := AVG(books)\n",
    "    FROM weights\n",
    "    WHERE student > 0\n",
    "    AND   books > 0;\n",
    "\n",
    "    SET @numerator   := @sum_xy - (@sum_x*@sum_y)/@n;\n",
    "    SET @denominator := @sum_xx - (@sum_X*@sum_x)/@n;\n",
    "\n",
    "    SET @m := @numerator/@denominator;\n",
    "    SET @b := @mean_y - @m*@mean_x;\n",
    "\n",
    "    SET SQL_SAFE_UPDATES := 0;\n",
    "\n",
    "    -- Replace missing student weights.\n",
    "\n",
    "    UPDATE weights\n",
    "    SET student := (books - @b)/@m\n",
    "    WHERE student < 0;\n",
    "\n",
    "    -- Replace missing book weights.\n",
    "\n",
    "    UPDATE weights\n",
    "    SET books := @m*student + @b\n",
    "    WHERE books < 0;\n",
    "\n",
    "    COMMIT;\n",
    "    \"\"\"\n",
    "      )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aaf09002-8ba7-4a51-a308-90b1de48536c",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Clean the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1be98fe6-c2cd-411f-9c8d-4bae726cf28a",
   "metadata": {},
   "outputs": [],
   "source": [
    "execute_multiple_SQL(cursor, sql)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1548f974-7183-4178-9b8a-e3a9804ef8c0",
   "metadata": {},
   "source": [
    "## The cleaned `weights` table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "195ff24e-b157-4aa8-b4bd-6151ab4ed348",
   "metadata": {},
   "outputs": [],
   "source": [
    "rows = display_and_return(cursor)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b451c3f1-7026-4ad2-8d9c-25a74fba42aa",
   "metadata": {},
   "source": [
    "## Obtain the slope `m` and y intercept `b`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cd00ce25-d868-40be-bd63-893ccfeef95e",
   "metadata": {},
   "outputs": [],
   "source": [
    "cursor.execute('SELECT @m, @b')\n",
    "result = cursor.fetchone()\n",
    "\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8d4217a2-b8de-4463-b53b-71b0c6c99d26",
   "metadata": {},
   "outputs": [],
   "source": [
    "m, b = result\n",
    "\n",
    "print(f'      slope m = {m:4.2f}')\n",
    "print(f'y intercept b = {b:4.2f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3fca5c49-214d-42e1-82a9-d0e6ca715e21",
   "metadata": {},
   "outputs": [],
   "source": [
    "cursor.execute('SELECT MAX(student) FROM weights')\n",
    "result = cursor.fetchone()\n",
    "\n",
    "max_student_weight = result[0]\n",
    "print(f'{max_student_weight = }')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27a03659-f2c5-4107-a91b-88b0e1285b70",
   "metadata": {},
   "source": [
    "## The regression line\n",
    "#### Assume the dataset is so large that we don't want to download it to draw a scatter plot. We only download three values: m, b, and the maximum student weight."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "013bd968-cb00-4320-b04f-9c3c5427140b",
   "metadata": {},
   "outputs": [],
   "source": [
    "draw_graph(max_student_weight, m, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15e97b63-d9fc-4aee-a02a-b14f67d222ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "cursor.close()\n",
    "conn.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26564040-c4f6-433b-a101-fd03568ea0a0",
   "metadata": {},
   "source": [
    "#### (c) 2023 by Ronald Mak"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1d207a1-4a4e-4a55-880a-bbc18e3efce0",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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