Notebooks/04_JupyterSQL.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction to Databases\n",
    "\n",
    "### Pandas, SQL and Jupyter "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install -U -q ipython-sql sqlalchemy pandas_profiling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### iPython magic commands (%sql, %%sql) to enable SQL syntax in the iPython interpreter.\n",
    "Based on [this](https://towardsdatascience.com/how-to-install-mysql-and-create-an-employees-sample-database-80dd9c5d4767) post"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Installing packages:  \n",
    "\n",
    "| Package              | Conda                                       | PIP                                   |\n",
    "|----------------------|---------------------------------------------|---------------------------------------|\n",
    "| ipython-sql          | !conda install -c condo-forge ipython-sql   | !pip install ipython-sql              |\n",
    "| sqlalchemy           | !conda install -c anaconda sqlalchemy       | !pip install sqlalchemy               |\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "SQLAlchemy supports many dialects and drivers; [click here for a full list](https://docs.sqlalchemy.org/en/13/dialects/).  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| Dialect              | Driver    | Conda Install Driver                  |\n",
    "|----------------------|-----------|---------------------------------------|\n",
    "| MySQL                | PyMySQL   | conda install -c anaconda pymysql     |\n",
    "| PostgreSQL           | Pyscopg2  | conda install -c conda-forge psycopg2 |\n",
    "| SQLite               | Pysqlite  | conda install -c prometeia pysqlite   |\n",
    "| Oracle               | Cx Oracle | conda install -c anaconda cx_oracle   |\n",
    "| Microsoft SQL Server | Pyodbc    | conda install -c conda-forge pyodbc   |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Connecting to a Database\n",
    "The [Engine](https://docs.sqlalchemy.org/en/13/core/connections.html#sqlalchemy.engine.Engine) is the starting point for any SQLAlchemy application. The typical form of a database URL using SQLAlchemy is:  \n",
    "\n",
    "> dialect+driver://username:password@host:port/database"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For secure access, you may dynamically access your credentials to avoid storing your password in the notebook itself.  \n",
    "\n",
    "Here is an example of how to connect to a local MySQL database. We will be using [this example database](https://github.com/datacharmer/test_db):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load the ipython-sql extension\n",
    "%load_ext sql"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Option1: Show credentials\n",
    "#%sql mysql+pymysql://user:password@localhost:3306/database_name\n",
    "#%sql mysql+pymysql://root:password@localhost:3306/employees"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For secure access, you may dynamically access your credentials to avoid storing your password in the notebook itself."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      " ·········\n"
     ]
    }
   ],
   "source": [
    "# Option2: Hide password using getpass\n",
    "import getpass\n",
    "\n",
    "password = getpass.getpass()\n",
    "user = 'root'\n",
    "database = 'employees'\n",
    "\n",
    "connection_string = f'mysql+pymysql://{user}:{password}@localhost:3306/{database}'\n",
    "%sql $connection_string"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Executing SQL Queries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * mysql+pymysql://root:***@localhost:3306/employees\n",
      "10 rows affected.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>salary</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>158220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>157821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>156286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>155709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>155513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>155377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>155190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>154888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>154885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>154459</td>\n",
       "    </tr>\n",
       "</table>"
      ],
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       " (155190,),\n",
       " (154888,),\n",
       " (154885,),\n",
       " (154459,)]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# single-line query\n",
    "%sql SELECT salary FROM salaries ORDER BY salary DESC LIMIT 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * mysql+pymysql://root:***@localhost:3306/employees\n",
      "10 rows affected.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>salary</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>158220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>157821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>156286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>155709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>155513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>155377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>155190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>154888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>154885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>154459</td>\n",
       "    </tr>\n",
       "</table>"
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      "text/plain": [
       "[(158220,),\n",
       " (157821,),\n",
       " (156286,),\n",
       " (155709,),\n",
       " (155513,),\n",
       " (155377,),\n",
       " (155190,),\n",
       " (154888,),\n",
       " (154885,),\n",
       " (154459,)]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql # multi-line query (use double %%)\n",
    "SELECT salary\n",
    "FROM salaries\n",
    "ORDER BY salary DESC\n",
    "LIMIT 10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Assignment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * mysql+pymysql://root:***@localhost:3306/employees\n",
      "10 rows affected.\n"
     ]
    }
   ],
   "source": [
    "# assign to variable (single-line)\n",
    "top_10_salaries = %sql SELECT salary FROM salaries ORDER BY salary DESC LIMIT 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# assign to variable (multi-line)\n",
    "# the << operator captures query results in a local variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * mysql+pymysql://root:***@localhost:3306/employees\n",
      "10 rows affected.\n",
      "Returning data to local variable top_10_salaries\n"
     ]
    }
   ],
   "source": [
    "%%sql top_10_salaries <<\n",
    "SELECT salary\n",
    "FROM salaries\n",
    "ORDER BY salary DESC\n",
    "LIMIT 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th>salary</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>158220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>157821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>156286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>155709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>155513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>155377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>155190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>154888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>154885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td>154459</td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "[(158220,),\n",
       " (157821,),\n",
       " (156286,),\n",
       " (155709,),\n",
       " (155513,),\n",
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       " (155190,),\n",
       " (154888,),\n",
       " (154885,),\n",
       " (154459,)]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_10_salaries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pandas DataFrames"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Although the results of 'top_10_salaries' looks like a DataFrame, it's not, it's a `sql.run.ResultSet`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sql.run.ResultSet"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(top_10_salaries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# construct Pandas DataFrame\n",
    "df = top_10_salaries.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>158220</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>157821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>156286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>155709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>155513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>155377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>155190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>154888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>154885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>154459</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   salary\n",
       "0  158220\n",
       "1  157821\n",
       "2  156286\n",
       "3  155709\n",
       "4  155513\n",
       "5  155377\n",
       "6  155190\n",
       "7  154888\n",
       "8  154885\n",
       "9  154459"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can automatically return Pandas DataFrames by changing the configuration as seen below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# return Pandas DataFrames instead of regular result sets\n",
    "%config SqlMagic.autopandas=True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's test it out by querying 1000 rows from the salary table and plotting a histogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * mysql+pymysql://root:***@localhost:3306/employees\n",
      "1000 rows affected.\n",
      "Returning data to local variable salaries\n"
     ]
    }
   ],
   "source": [
    "%%sql salaries <<\n",
    "SELECT *\n",
    "FROM salaries\n",
    "LIMIT 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot histogram\n",
    "salaries['salary'].plot(kind='hist', figsize=(12,8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take it one step further by analyzing our query results with [Pandas Profiling](https://pypi.org/project/pandas-profiling/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * mysql+pymysql://root:***@localhost:3306/employees\n",
      "10000 rows affected.\n"
     ]
    }
   ],
   "source": [
    "df = %sql SELECT * FROM salaries LIMIT 10000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5352f46b20a94ff29dde1457c5e9258d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Summarize dataset:   0%|          | 0/17 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "de186515734a434eaaad164ce3d0df9a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Generate report structure:   0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3e7dbf2da2f64130a06ce13d6a528142",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Render HTML:   0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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GradientType=0);background-repeat:repeat-x;border-color:#dcdcdc;-webkit-box-shadow:inset 0 1px 3px rgba(0,0,0,.05),0 1px 0 rgba(255,255,255,.1);box-shadow:inset 0 1px 3px rgba(0,0,0,.05),0 1px 0 rgba(255,255,255,.1)}\n",
       "/*# sourceMappingURL=bootstrap-theme.min.css.map */        &lt;/style&gt;&lt;style&gt;body {\n",
       "  padding-top: 80px;\n",
       "}\n",
       ".content .container-fluid{\n",
       "    margin-left: 20px !important;\n",
       "    margin-right: 20px !important;\n",
       "    margin-bottom: 20px;\n",
       "}\n",
       "\n",
       ".page-header{\n",
       "    border:0 !important;\n",
       "}\n",
       "\n",
       ".row.variable, .section-items &gt; .row {\n",
       "    border: 1px solid #e1e1e8;\n",
       "    border-top: hidden;\n",
       "}\n",
       "\n",
       ".row.spacing{\n",
       "    padding: 2em 1em;\n",
       "}\n",
       "\n",
       ".row.header {\n",
       "    border-bottom: 1px solid #e1e1e8;\n",
       "    /*background-color: #f5f5f5;*/\n",
       "    padding-left: 2em;\n",
       "}\n",
       "\n",
       "\n",
       ".dl-horizontal dt {\n",
       "    text-align: left;\n",
       "    padding-right: 1em;\n",
       "    white-space: normal;\n",
       "}\n",
       "\n",
       ".dl-horizontal dd {\n",
       "    margin-left: 0;\n",
       "}\n",
       "\n",
       ".col-md-12 {\n",
       "    padding-left: 2em;\n",
       "}\n",
       "\n",
       ".indent {\n",
       "    margin-left: 1em;\n",
       "}\n",
       "\n",
       ".center-img {\n",
       "    margin-left: auto !important;\n",
       "    margin-right: auto !important;\n",
       "    display: block;\n",
       "}\n",
       "\n",
       "/* Table example_values */\n",
       "table.example_values {\n",
       "    border: 0;\n",
       "}\n",
       "\n",
       ".example_values th {\n",
       "    border: 0;\n",
       "    padding: 0;\n",
       "    color: #555;\n",
       "    font-weight: 600;\n",
       "}\n",
       "\n",
       ".example_values tr, .example_values td {\n",
       "    border: 0;\n",
       "    padding: 0;\n",
       "    color: #555;\n",
       "}\n",
       "\n",
       "/* STATS */\n",
       "table.stats, table.sample, table.duplicate{\n",
       "    border: 0;\n",
       "}\n",
       "\n",
       ".stats tr, .sample tr, .duplicate tr {\n",
       "    border: 0;\n",
       "}\n",
       "\n",
       ".stats th, .stats td{\n",
       "    color: #555;\n",
       "    border: 0;\n",
       "}\n",
       "\n",
       ".stats th {\n",
       "    padding: 0 2em 0 0;\n",
       "    font-weight: 600;\n",
       "}\n",
       "\n",
       ".stats td {\n",
       "    padding: 1px;\n",
       "}\n",
       "\n",
       "\n",
       "/* Sample table */\n",
       "table.sample, table.duplicate{\n",
       "    margin-bottom: 2em;\n",
       "    margin-left: 1em;\n",
       "}\n",
       "\n",
       ".sample td, .sample th, .duplicate td, .duplicate th {\n",
       "    padding: 0.5em;\n",
       "    white-space: nowrap;\n",
       "    border: 0;\n",
       "\n",
       "}\n",
       "\n",
       ".sample thead, .duplicate thead {\n",
       "    border-top: 0;\n",
       "    border-bottom: 2px solid #ddd;\n",
       "}\n",
       "\n",
       ".sample td, .duplicate td {\n",
       "    width: 100%;\n",
       "}\n",
       "\n",
       "\n",
       "/* There is no good solution available to make the divs equal height and then center ... */\n",
       ".histogram {\n",
       "    margin-top: 3em;\n",
       "}\n",
       "\n",
       "/* Freq table */\n",
       "table.freq {\n",
       "    margin-bottom: 2em;\n",
       "    border: 0;\n",
       "}\n",
       "\n",
       "table.freq th, table.freq tr, table.freq td {\n",
       "    border: 0;\n",
       "    padding: 0;\n",
       "}\n",
       "\n",
       ".freq thead {\n",
       "    font-weight: 600;\n",
       "    white-space: nowrap;\n",
       "    overflow: hidden;\n",
       "    text-overflow: ellipsis;\n",
       "\n",
       "}\n",
       "\n",
       "/* Freq mini */\n",
       ".freq.mini td {\n",
       "    width: 50%;\n",
       "    padding: 1px;\n",
       "    font-size: 12px;\n",
       "\n",
       "}\n",
       "\n",
       "table.freq.mini {\n",
       "    width: 100%;\n",
       "}\n",
       "\n",
       ".freq.mini th {\n",
       "    overflow: hidden;\n",
       "    text-overflow: ellipsis;\n",
       "    white-space: nowrap;\n",
       "    max-width: 5em;\n",
       "    font-weight: 400;\n",
       "    text-align: right;\n",
       "    padding-right: 0.5em;\n",
       "}\n",
       "\n",
       "/* Message classes */\n",
       ".missing {\n",
       "    color: #a94442;\n",
       "}\n",
       "\n",
       ".alert, .alert &gt; th, .alert &gt; td {\n",
       "    color: #a94442;\n",
       "}\n",
       "\n",
       ".ignore {\n",
       "    opacity: 0.4;\n",
       "}\n",
       "\n",
       "/* Bars in tables */\n",
       ".freq.table{\n",
       "    table-layout: fixed;\n",
       "}\n",
       "\n",
       ".freq:not(.mini) tr td:nth-child(1), .freq:not(.mini) tr th:nth-child(1){\n",
       "    width: auto;\n",
       "    max-width: none;\n",
       "\n",
       "    white-space: nowrap;\n",
       "    overflow: hidden;\n",
       "    text-overflow: ellipsis;\n",
       "}\n",
       "\n",
       ".freq:not(.mini) tr td:nth-child(2), .freq:not(.mini) tr td:nth-child(3), .freq:not(.mini) tr th:nth-child(2), .freq:not(.mini) tr th:nth-child(3){\n",
       "    width: 100px;\n",
       "    text-align: right;\n",
       "}\n",
       ".freq:not(.mini) tr td:nth-child(4), .freq:not(.mini) tr th:nth-child(4){\n",
       "    width:200px;\n",
       "}\n",
       "\n",
       ".freq .bar {\n",
       "    float: left;\n",
       "    width: 0;\n",
       "    height: 100%;\n",
       "    line-height: 20px;\n",
       "    color: #fff;\n",
       "    text-align: center;\n",
       "    background-color: #337ab7;\n",
       "    border-radius: 3px;\n",
       "    margin-right: 4px;\n",
       "}\n",
       "\n",
       ".other .bar {\n",
       "    background-color: #999;\n",
       "}\n",
       "\n",
       ".missing .bar {\n",
       "    background-color: #a94442;\n",
       "}\n",
       "\n",
       ".tooltip-inner {\n",
       "    width: 100%;\n",
       "    white-space: nowrap;\n",
       "    text-align: left;\n",
       "}\n",
       "\n",
       ".extrapadding {\n",
       "    padding: 2em;\n",
       "}\n",
       "\n",
       ".variable .h4 {\n",
       "    text-overflow: ellipsis;\n",
       "    display:inline-block;\n",
       "    width: calc(90%); /* The trick is here! */\n",
       "    overflow:hidden;\n",
       "}\n",
       "\n",
       ".variable.ignore .h4{\n",
       "    text-decoration: line-through;\n",
       "}\n",
       "\n",
       ".table-responsive{\n",
       "    overflow: scroll;\n",
       "    width: 100%;\n",
       "    overflow-y: hidden;\n",
       "}\n",
       ".img-responsive{\n",
       "    max-width: 99%;\n",
       "}\n",
       ".footer-text{\n",
       "    padding:20px;\n",
       "}\n",
       "\n",
       "table.list-warnings td{\n",
       "    padding-right:10px;\n",
       "}\n",
       "\n",
       "a.anchor-pos {\n",
       "    display: block;\n",
       "    position: relative;\n",
       "    top: -70px;\n",
       "    visibility: hidden;\n",
       "}\n",
       "\n",
       "a.anchor-pos-variable{\n",
       "    /*top: -70px;*/\n",
       "}\n",
       "\n",
       "#sample-container, #duplicate-container{\n",
       "    overflow: auto;\n",
       "    width: 100%;\n",
       "    overflow-y: hidden;\n",
       "}\n",
       "\n",
       "#overview-content td, #overview-content th{\n",
       "    border-top: 0;\n",
       "    line-height: 1;\n",
       "}\n",
       "\n",
       ".variable-description{\n",
       "    color: #777;\n",
       "    font-size: 10pt;\n",
       "    margin-top: 10px;\n",
       "    font-style: italic;\n",
       "}\n",
       "\n",
       "select.multiple{\n",
       "    width: 180px;\n",
       "    height: 500px;\n",
       "    margin: 10px 0;\n",
       "}\n",
       "\n",
       ".named-list-item{\n",
       "    padding: 1em;\n",
       "}\n",
       "\n",
       "/* not printing tabs */\n",
       "@media print {\n",
       "    .tab-content &gt; .tab-pane, .collapse {\n",
       "        display: block !important;\n",
       "        opacity: 1 !important;\n",
       "        visibility: visible !important;\n",
       "        /*page-break-after: always;*/\n",
       "        page-break-after: right;\n",
       "        page-break-before: avoid;\n",
       "    }\n",
       "\n",
       "    .nav-pills, .nav-tabs, button[data-toggle=&quot;collapse&quot;], .mini, .col-sm-3 img {\n",
       "        display:none !important;\n",
       "    }\n",
       "\n",
       "    a[download=&quot;config.yml&quot;]:after {\n",
       "        content: none !important;\n",
       "    }\n",
       "\n",
       "    .row {\n",
       "        border: 0 !important;\n",
       "    }\n",
       "}\n",
       "\n",
       ".text-placeholder {\n",
       "    display: inline-block;\n",
       "    background-color: #444;\n",
       "    height: 12px;\n",
       "    border-radius: 100px;\n",
       "    margin: 5px 0;\n",
       "    min-width: 200px;\n",
       "    opacity: .1;\n",
       "}&lt;/style&gt;&lt;/head&gt;&lt;body&gt;&lt;a class=anchor-pos id=top&gt;&lt;/a&gt;&lt;nav class=&quot;navbar navbar-default navbar-fixed-top&quot;&gt;&lt;div class=container-fluid&gt;&lt;div class=navbar-header&gt;&lt;button type=button class=&quot;navbar-toggle collapsed&quot; data-toggle=collapse data-target=#navbar aria-expanded=false aria-controls=navbar&gt;&lt;span class=sr-only&gt;Toggle navigation&lt;/span&gt;&lt;span class=icon-bar&gt;&lt;/span&gt;&lt;span class=icon-bar&gt;&lt;/span&gt;&lt;span class=icon-bar&gt;&lt;/span&gt;&lt;/button&gt;&lt;a class=&quot;navbar-brand anchor&quot; href=#top&gt;Pandas Profiling Report&lt;/a&gt;&lt;/div&gt;&lt;div id=navbar class=&quot;navbar-collapse collapse&quot;&gt;&lt;ul class=&quot;nav navbar-nav navbar-right&quot;&gt;&lt;li&gt;&lt;a class=anchor href=#overview&gt;Overview&lt;/a&gt;&lt;/li&gt;&lt;li&gt;&lt;a class=anchor href=#variables&gt;Variables&lt;/a&gt;&lt;/li&gt;&lt;li&gt;&lt;a class=anchor href=#interactions&gt;Interactions&lt;/a&gt;&lt;/li&gt;&lt;li&gt;&lt;a class=anchor href=#correlations&gt;Correlations&lt;/a&gt;&lt;/li&gt;&lt;li&gt;&lt;a class=anchor href=#missing&gt;Missing values&lt;/a&gt;&lt;/li&gt;&lt;li&gt;&lt;a class=anchor href=#sample&gt;Sample&lt;/a&gt;&lt;/li&gt;&lt;li&gt;&lt;a class=anchor href=#duplicate&gt;Duplicate rows&lt;/a&gt;&lt;/li&gt;&lt;/ul&gt;&lt;/div&gt;&lt;/div&gt;&lt;/nav&gt;&lt;div class=content&gt;&lt;div class=container-fluid&gt;&lt;div class=&quot;row header&quot;&gt;&lt;a class=anchor-pos id=overview&gt;&lt;/a&gt;&lt;h1 class=page-header&gt;Overview&lt;/h1&gt;&lt;/div&gt;&lt;div class=section-items&gt;&lt;div class=&quot;row spacing&quot;&gt;&lt;ul class=&quot;nav nav-pills&quot; role=tablist&gt;&lt;li role=presentation class=active&gt;&lt;a href=#overview-dataset_overview aria-controls=overview-dataset_overview role=tab data-toggle=tab&gt;Overview&lt;/a&gt;&lt;/li&gt;&lt;li role=presentation&gt;&lt;a href=#overview-warnings aria-controls=overview-warnings role=tab data-toggle=tab&gt;Warnings &lt;span class=badge&gt;3&lt;/span&gt;&lt;/a&gt;&lt;/li&gt;&lt;li role=presentation&gt;&lt;a href=#overview-reproduction aria-controls=overview-reproduction role=tab data-toggle=tab&gt;Reproduction&lt;/a&gt;&lt;/li&gt;&lt;/ul&gt;&lt;div class=tab-content style=&quot;padding-top: 10px;&quot;&gt;&lt;div role=tabpanel class=&quot;tab-pane col-sm-12 active&quot; id=overview-dataset_overview&gt;&lt;div class=col-sm-6&gt;&lt;p class=h4&gt;Dataset statistics&lt;/p&gt;&lt;table class=&quot;table table-condensed stats&quot;&gt;&lt;tbody&gt;&lt;tr&gt;&lt;th&gt;Number of variables&lt;/th&gt;&lt;td&gt;4&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Number of observations&lt;/th&gt;&lt;td&gt;10000&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Missing cells&lt;/th&gt;&lt;td&gt;0&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Missing cells (%)&lt;/th&gt;&lt;td&gt;0.0%&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Duplicate rows&lt;/th&gt;&lt;td&gt;1&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Duplicate rows (%)&lt;/th&gt;&lt;td&gt;&lt; 0.1%&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Total size in memory&lt;/th&gt;&lt;td&gt;312.6 KiB&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Average record size in memory&lt;/th&gt;&lt;td&gt;32.0 B&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;&lt;/div&gt;&lt;div class=col-sm-6&gt;&lt;p class=h4&gt;Variable types&lt;/p&gt;&lt;table class=&quot;table table-condensed stats&quot;&gt;&lt;tbody&gt;&lt;tr&gt;&lt;th&gt;Numeric&lt;/th&gt;&lt;td&gt;2&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Unsupported&lt;/th&gt;&lt;td&gt;2&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;&lt;/div&gt;&lt;/div&gt;&lt;div role=tabpanel class=&quot;tab-pane col-sm-12&quot; id=overview-warnings&gt;&lt;table class=&quot;table table-condensed list-warnings&quot;&gt;&lt;p class=h4&gt;Warnings&lt;/p&gt;&lt;tr style=border-top:0&gt;&lt;td&gt; Dataset has 1 (&lt; 0.1%) duplicate rows &lt;/td&gt;&lt;td&gt;&lt;span class=&quot;label label-default&quot;&gt;Duplicates&lt;/span&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td&gt;&lt;a class=anchor href=#pp_var_-5264436446505197752&gt;&lt;code&gt;from_date&lt;/code&gt;&lt;/a&gt; is an unsupported type, check if it needs cleaning or further analysis &lt;/td&gt;&lt;td&gt;&lt;span class=&quot;label label-warning&quot;&gt;Unsupported&lt;/span&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td&gt;&lt;a class=anchor href=#pp_var_-7265812911116854072&gt;&lt;code&gt;to_date&lt;/code&gt;&lt;/a&gt; is an unsupported type, check if it needs cleaning or further analysis &lt;/td&gt;&lt;td&gt;&lt;span class=&quot;label label-warning&quot;&gt;Unsupported&lt;/span&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/table&gt;&lt;/div&gt;&lt;div role=tabpanel class=&quot;tab-pane col-sm-12&quot; id=overview-reproduction&gt;&lt;div class=col-sm-12&gt;&lt;p class=h4&gt;Reproduction&lt;/p&gt;&lt;table class=&quot;table table-condensed stats&quot;&gt;&lt;tbody&gt;&lt;tr&gt;&lt;th&gt;Analysis started&lt;/th&gt;&lt;td&gt;2021-02-06 17:29:35.365137&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Analysis finished&lt;/th&gt;&lt;td&gt;2021-02-06 17:29:37.370884&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Duration&lt;/th&gt;&lt;td&gt;2.01 seconds&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Software version&lt;/th&gt;&lt;td&gt;&lt;a href=https://github.com/pandas-profiling/pandas-profiling&gt;pandas-profiling v2.10.0&lt;/a&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Download configuration&lt;/th&gt;&lt;td&gt;&lt;a download=config.yaml 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class=&quot;row header&quot;&gt;&lt;a class=anchor-pos id=variables&gt;&lt;/a&gt;&lt;h1 class=page-header&gt;Variables&lt;/h1&gt;&lt;/div&gt;&lt;div class=section-items&gt;&lt;div class=&quot;row spacing&quot;&gt;&lt;a class=&quot;anchor-pos anchor-pos-variable&quot; id=pp_var_3310340365854999747&gt;&lt;/a&gt;&lt;div class=variable&gt;&lt;div class=col-sm-3&gt;&lt;p class=h4 title=emp_no&gt;&lt;a href=#pp_var_3310340365854999747&gt;emp_no&lt;/a&gt;&lt;br&gt;&lt;small&gt;Real number (&amp;Ropf;&lt;sub&gt;&amp;ge;0&lt;/sub&gt;)&lt;/small&gt;&lt;/p&gt;&lt;p class=variable-description&gt;&lt;/p&gt;&lt;/div&gt;&lt;div class=col-sm-3&gt;&lt;table class=&quot;table table-condensed stats&quot;&gt;&lt;tbody&gt;&lt;tr&gt;&lt;th&gt;Distinct&lt;/th&gt;&lt;td&gt;1053&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Distinct (%)&lt;/th&gt;&lt;td&gt;10.5%&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Missing&lt;/th&gt;&lt;td&gt;0&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Missing 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0.2% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=10469&gt;10469&lt;/td&gt;&lt;td&gt;18&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.2%&gt; &amp;nbsp; &lt;/div&gt; 0.2% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=10453&gt;10453&lt;/td&gt;&lt;td&gt;18&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.2%&gt; &amp;nbsp; &lt;/div&gt; 0.2% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=11038&gt;11038&lt;/td&gt;&lt;td&gt;18&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.2%&gt; &amp;nbsp; &lt;/div&gt; 0.2% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=10768&gt;10768&lt;/td&gt;&lt;td&gt;18&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.2%&gt; &amp;nbsp; &lt;/div&gt; 0.2% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=10571&gt;10571&lt;/td&gt;&lt;td&gt;18&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.2%&gt; &amp;nbsp; &lt;/div&gt; 0.2% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=10137&gt;10137&lt;/td&gt;&lt;td&gt;18&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.2%&gt; &amp;nbsp; &lt;/div&gt; 0.2% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=10739&gt;10739&lt;/td&gt;&lt;td&gt;18&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.2%&gt; &amp;nbsp; &lt;/div&gt; 0.2% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=10550&gt;10550&lt;/td&gt;&lt;td&gt;18&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.2%&gt; &amp;nbsp; &lt;/div&gt; 0.2% &lt;/td&gt;&lt;/tr&gt;&lt;tr class=other&gt;&lt;td title=&quot;Other values (1043)&quot;&gt;Other values (1043)&lt;/td&gt;&lt;td&gt;9820&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:100.0%&gt; 98.2% &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;&lt;/div&gt;&lt;div role=tabpanel class=&quot;tab-pane col-sm-12&quot; id=3310340365854999747bottom-3310340365854999747extreme_values&gt;&lt;div class=&quot;row spacing&quot;&gt;&lt;ul class=&quot;nav nav-tabs&quot; role=tablist&gt;&lt;li role=presentation class=active&gt;&lt;a href=#3310340365854999747extreme_values-3310340365854999747firstn aria-controls=3310340365854999747extreme_values-3310340365854999747firstn role=tab data-toggle=tab&gt;Minimum 5 values&lt;/a&gt;&lt;/li&gt;&lt;li role=presentation&gt;&lt;a href=#3310340365854999747extreme_values-3310340365854999747lastn aria-controls=3310340365854999747extreme_values-3310340365854999747lastn role=tab data-toggle=tab&gt;Maximum 5 values&lt;/a&gt;&lt;/li&gt;&lt;/ul&gt;&lt;div class=tab-content&gt;&lt;div role=tabpanel class=&quot;tab-pane col-sm-12 active&quot; id=3310340365854999747extreme_values-3310340365854999747firstn&gt;&lt;table class=&quot;freq table table-hover table-striped&quot;&gt;&lt;thead&gt;&lt;tr&gt;&lt;td&gt;Value&lt;/td&gt;&lt;td&gt;Count&lt;/td&gt;&lt;td&gt;Frequency (%)&lt;/td&gt;&lt;/tr&gt;&lt;/thead&gt;&lt;tbody&gt;&lt;tr class&gt;&lt;td title=10001&gt;10001&lt;/td&gt;&lt;td&gt;17&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:100.0%&gt; 0.2% &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=10002&gt;10002&lt;/td&gt;&lt;td&gt;6&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:35.3%&gt; &amp;nbsp; &lt;/div&gt; 0.1% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=10003&gt;10003&lt;/td&gt;&lt;td&gt;7&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:41.2%&gt; 0.1% &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=10004&gt;10004&lt;/td&gt;&lt;td&gt;16&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:94.1%&gt; 0.2% &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=10005&gt;10005&lt;/td&gt;&lt;td&gt;13&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:76.5%&gt; 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&lt;/div&gt;&lt; 0.1% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=49154&gt;49154&lt;/td&gt;&lt;td&gt;3&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.0%&gt; &amp;nbsp; &lt;/div&gt;&lt; 0.1% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=53367&gt;53367&lt;/td&gt;&lt;td&gt;3&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.0%&gt; &amp;nbsp; &lt;/div&gt;&lt; 0.1% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=43283&gt;43283&lt;/td&gt;&lt;td&gt;3&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.0%&gt; &amp;nbsp; &lt;/div&gt;&lt; 0.1% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=80937&gt;80937&lt;/td&gt;&lt;td&gt;3&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.0%&gt; &amp;nbsp; &lt;/div&gt;&lt; 0.1% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=50195&gt;50195&lt;/td&gt;&lt;td&gt;3&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.0%&gt; &amp;nbsp; &lt;/div&gt;&lt; 0.1% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=47995&gt;47995&lt;/td&gt;&lt;td&gt;3&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.0%&gt; &amp;nbsp; &lt;/div&gt;&lt; 0.1% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=77923&gt;77923&lt;/td&gt;&lt;td&gt;3&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.0%&gt; &amp;nbsp; &lt;/div&gt;&lt; 0.1% &lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=72796&gt;72796&lt;/td&gt;&lt;td&gt;3&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:0.0%&gt; &amp;nbsp; &lt;/div&gt;&lt; 0.1% &lt;/td&gt;&lt;/tr&gt;&lt;tr class=other&gt;&lt;td title=&quot;Other values (8848)&quot;&gt;Other values (8848)&lt;/td&gt;&lt;td&gt;9656&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:100.0%&gt; 96.6% &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;&lt;/div&gt;&lt;div role=tabpanel class=&quot;tab-pane col-sm-12&quot; id=6524502182968207931bottom-6524502182968207931extreme_values&gt;&lt;div class=&quot;row spacing&quot;&gt;&lt;ul class=&quot;nav nav-tabs&quot; role=tablist&gt;&lt;li role=presentation class=active&gt;&lt;a href=#6524502182968207931extreme_values-6524502182968207931firstn aria-controls=6524502182968207931extreme_values-6524502182968207931firstn role=tab data-toggle=tab&gt;Minimum 5 values&lt;/a&gt;&lt;/li&gt;&lt;li role=presentation&gt;&lt;a href=#6524502182968207931extreme_values-6524502182968207931lastn aria-controls=6524502182968207931extreme_values-6524502182968207931lastn role=tab data-toggle=tab&gt;Maximum 5 values&lt;/a&gt;&lt;/li&gt;&lt;/ul&gt;&lt;div class=tab-content&gt;&lt;div role=tabpanel class=&quot;tab-pane col-sm-12 active&quot; id=6524502182968207931extreme_values-6524502182968207931firstn&gt;&lt;table class=&quot;freq table table-hover table-striped&quot;&gt;&lt;thead&gt;&lt;tr&gt;&lt;td&gt;Value&lt;/td&gt;&lt;td&gt;Count&lt;/td&gt;&lt;td&gt;Frequency (%)&lt;/td&gt;&lt;/tr&gt;&lt;/thead&gt;&lt;tbody&gt;&lt;tr class&gt;&lt;td title=39265&gt;39265&lt;/td&gt;&lt;td&gt;1&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:100.0%&gt;&lt; 0.1% &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=39507&gt;39507&lt;/td&gt;&lt;td&gt;1&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:100.0%&gt;&lt; 0.1% &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=39520&gt;39520&lt;/td&gt;&lt;td&gt;1&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:100.0%&gt;&lt; 0.1% &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=39528&gt;39528&lt;/td&gt;&lt;td&gt;1&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:100.0%&gt;&lt; 0.1% &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=39530&gt;39530&lt;/td&gt;&lt;td&gt;1&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:100.0%&gt;&lt; 0.1% &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;&lt;/div&gt;&lt;div role=tabpanel class=&quot;tab-pane col-sm-12&quot; id=6524502182968207931extreme_values-6524502182968207931lastn&gt;&lt;table class=&quot;freq table table-hover table-striped&quot;&gt;&lt;thead&gt;&lt;tr&gt;&lt;td&gt;Value&lt;/td&gt;&lt;td&gt;Count&lt;/td&gt;&lt;td&gt;Frequency (%)&lt;/td&gt;&lt;/tr&gt;&lt;/thead&gt;&lt;tbody&gt;&lt;tr class&gt;&lt;td title=136004&gt;136004&lt;/td&gt;&lt;td&gt;1&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:100.0%&gt;&lt; 0.1% &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=135407&gt;135407&lt;/td&gt;&lt;td&gt;1&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:100.0%&gt;&lt; 0.1% &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=131431&gt;131431&lt;/td&gt;&lt;td&gt;1&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:100.0%&gt;&lt; 0.1% &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr class&gt;&lt;td title=127479&gt;127479&lt;/td&gt;&lt;td&gt;1&lt;/td&gt;&lt;td&gt;&lt;div class=bar style=width:100.0%&gt;&lt; 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class=&quot;row header&quot;&gt;&lt;a class=anchor-pos id=duplicate&gt;&lt;/a&gt;&lt;h1 class=page-header&gt;Duplicate rows&lt;/h1&gt;&lt;/div&gt;&lt;div class=section-items&gt;&lt;div class=&quot;row spacing&quot;&gt;&lt;h2 class=indent&gt;Most frequent&lt;/h2&gt;&lt;div id=duplicate-container class=col-sm-12&gt;&lt;table border=1 class=&quot;dataframe duplicate table table-striped&quot;&gt;&lt;thead&gt;&lt;tr style=&quot;text-align: right;&quot;&gt;&lt;th&gt;&lt;/th&gt;&lt;th&gt;emp_no&lt;/th&gt;&lt;th&gt;salary&lt;/th&gt;&lt;th&gt;count&lt;/th&gt;&lt;/tr&gt;&lt;/thead&gt;&lt;tbody&gt;&lt;tr&gt;&lt;th&gt;0&lt;/th&gt;&lt;td&gt;10560&lt;/td&gt;&lt;td&gt;44789&lt;/td&gt;&lt;td&gt;2&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;footer&gt;&lt;div class=container-fluid&gt;&lt;div class=&quot;row center-block footer-text&quot;&gt;&lt;p class=&quot;text-muted text-center&quot;&gt;Report generated with &lt;a href=https://github.com/pandas-profiling/pandas-profiling&gt;pandas-profiling&lt;/a&gt;.&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/footer&gt;&lt;script&gt;\n",
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       "$(function () {\n",
       "    $(&#x27;[data-toggle=&quot;tooltip&quot;]&#x27;).tooltip();\n",
       "});\n",
       "\n",
       "$(&quot;a[href^=&#x27;#&#x27;].anchor&quot;).on(&#x27;click&#x27;, function (e) {\n",
       "\n",
       "    // prevent default anchor click behavior\n",
       "    e.preventDefault();\n",
       "\n",
       "    // store hash\n",
       "    var hash = this.hash;\n",
       "\n",
       "    // animate\n",
       "    $(&#x27;html, body&#x27;).animate({\n",
       "        scrollTop: $(hash).offset().top\n",
       "    }, 300, function () {\n",
       "\n",
       "        // when done, add hash to url\n",
       "        // (default click behaviour)\n",
       "        window.location.hash = hash;\n",
       "    });\n",
       "\n",
       "});        &lt;/script&gt;&lt;/body&gt;&lt;/html&gt;\" frameborder=\"0\" allowfullscreen></iframe>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas_profiling import ProfileReport\n",
    "\n",
    "profile = ProfileReport(df, title='Pandas Profiling Report', html={'style':{'full_width':True}})\n",
    "profile.to_notebook_iframe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Limiting Results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Executing SQL queries via iPython is not as fast as using the command line or a SQL editor, but you can limit the query results (recommended)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# limits displayed results; entire set is still pulled into memory\n",
    "%config SqlMagic.displaylimit=10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# limits the result set (good for large sets that can slow down your browser)\n",
    "%config SqlMagic.autolimit=100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Commenting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Commenting is a bit tricky. **My recommendation is to not include any comments**, use markdown if possible.\n",
    "\n",
    "Normally you would use a `#` for Python comments or `--` for single-line in SQL and `/# #/` for block quotes.\n",
    "\n",
    "Furthermore, **commented lines have an effect**, even though the results don't display.\n",
    "\n",
    "Here's what seems to work and not work (at least in MySQL)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use Cases"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The query below will execute in ~1 second."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * mysql+pymysql://root:***@localhost:3306/employees\n",
      "10 rows affected.\n",
      "Returning data to local variable top_10_salaries\n"
     ]
    }
   ],
   "source": [
    "%%sql top_10_salaries <<\n",
    "SELECT salary\n",
    "FROM salaries\n",
    "ORDER BY salary DESC\n",
    "LIMIT 10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The same query with a comment will execute in ~25 seconds!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * mysql+pymysql://root:***@localhost:3306/employees\n",
      "10 rows affected.\n",
      "Returning data to local variable top_10_salaries\n"
     ]
    }
   ],
   "source": [
    "%%sql top_10_salaries <<\n",
    "SELECT salary\n",
    "FROM salaries\n",
    "# ORDER BY salary DESC\n",
    "LIMIT 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * mysql+pymysql://root:***@localhost:3306/employees\n",
      "10 rows affected.\n",
      "Returning data to local variable top_10_salaries\n"
     ]
    }
   ],
   "source": [
    "%%sql top_10_salaries <<\n",
    "# this comment will result in 0 rows affected!!\n",
    "SELECT salary\n",
    "FROM salaries\n",
    "ORDER BY salary DESC\n",
    "LIMIT 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (<ipython-input-30-eab2ee6caa5c>, line 3)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-30-eab2ee6caa5c>\"\u001b[0;36m, line \u001b[0;32m3\u001b[0m\n\u001b[0;31m    SELECT salary\u001b[0m\n\u001b[0m           ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "# comments before %%sql won't execute the query\n",
    "%%sql top_10_salaries <<\n",
    "SELECT salary\n",
    "FROM salaries\n",
    "ORDER BY salary DESC\n",
    "LIMIT 10                          #error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * mysql+pymysql://root:***@localhost:3306/employees\n",
      "10 rows affected.\n"
     ]
    }
   ],
   "source": [
    "# comments with %sql seem to work best\n",
    "top_10_salaries = %sql SELECT salary FROM salaries ORDER BY salary DESC LIMIT 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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