(2) Connecting_To_Structured.ipynb

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 "cells": [
  {
   "source": [
    "### Import Libraries"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyodbc as sql \n",
    "import pandas as pd\n"
   ]
  },
  {
   "source": [
    "### Define connection string to SQL Server"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "source_db_config = {\n",
    "    'Trusted_Connection': 'yes',\n",
    "    'driver': '{SQL Server}',\n",
    "    'server': '.',\n",
    "    'database': 'AdventureWorksDW2017',\n",
    "    'autocommit': True,\n",
    "}"
   ]
  },
  {
   "source": [
    "### Define the query to be used in the call to SQL"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sql_query = '''\n",
    "SELECT *, YEAR(OrderDate) AS OrderYear, MONTH(OrderDate) AS OrderMonth, DAY(OrderDate) AS OrderDay\n",
    "  FROM [AdventureWorksDW2017].[dbo].[FactInternetSales] \n",
    "'''"
   ]
  },
  {
   "source": [
    "### Set the connection"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "source_conn = sql.connect(**source_db_config)"
   ]
  },
  {
   "source": [
    "### Call SQL and load data to dataframe for storage"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_sql(sql_query, source_conn)\n",
    "print(df)"
   ]
  }
 ]
}