Merge pull request #25364 from rwestMSFT/rw-1223-python

Fix Python script to address issue 8415

Author: Stacyrch140

docs/machine-learning/data-exploration/python-plot-histogram.md

@@ -4,88 +4,106 @@ titleSuffix: SQL machine learning
 description: Learn how to create a histogram to visualize data using Python.
 author: WilliamDAssafMSFT
 ms.author: wiassaf
-ms.date: 07/14/2020
-ms.topic: how-to
+ms.reviewer: randolphwest
+ms.date: 12/23/2022
 ms.service: sql
 ms.subservice: machine-learning
+ms.topic: how-to
 monikerRange: ">=sql-server-2017||>=sql-server-linux-ver15||=azuresqldb-mi-current||=azuresqldb-current"
 ---
+# Plot histograms in Python
 
-# Plot histograms in Python 
 [!INCLUDE[SQL Server SQL DB SQL MI](../../includes/applies-to-version/sql-asdb-asdbmi.md)]
 
 This article describes how to plot data using the Python package [pandas'.hist()](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.hist.html). A SQL database is the source used to visualize the histogram data intervals that have consecutive, non-overlapping values.
 
-## Prerequisites:
+## Prerequisites
 
 ::: moniker range=">=sql-server-2017||>=sql-server-linux-ver15"
-* [SQL Server for Windows](../../database-engine/install-windows/install-sql-server.md) or [for Linux](../../linux/sql-server-linux-overview.md)
+- [SQL Server for Windows](../../database-engine/install-windows/install-sql-server.md) or [for Linux](../../linux/sql-server-linux-overview.md)
 ::: moniker-end
 
 ::: moniker range="=azuresqldb-current"
-* [Azure SQL Database](/azure/sql-database/sql-database-get-started-portal)
+- [Azure SQL Database](/azure/sql-database/sql-database-get-started-portal)
 ::: moniker-end
 
 ::: moniker range="=azuresqldb-mi-current"
-* [Azure SQL Managed Instance](/azure/azure-sql/managed-instance/instance-create-quickstart)
+- [Azure SQL Managed Instance](/azure/azure-sql/managed-instance/instance-create-quickstart)
 
-* [SQL Server Management Studio](../../ssms/download-sql-server-management-studio-ssms.md) for restoring the sample database to Azure SQL Managed Instance.
+- [SQL Server Management Studio](../../ssms/download-sql-server-management-studio-ssms.md) for restoring the sample database to Azure SQL Managed Instance.
 ::: moniker-end
 
-* Azure Data Studio. To install, see [Azure Data Studio](../../azure-data-studio/what-is-azure-data-studio.md).
+- Azure Data Studio. To install, see [Azure Data Studio](../../azure-data-studio/what-is-azure-data-studio.md).
 
-* [Restore sample DW database](../../samples/adventureworks-install-configure.md) to get sample data used in this article.
+- [Restore sample DW database](../../samples/adventureworks-install-configure.md) to get sample data used in this article.
 
-## Verify restored Database
+## Verify restored database
 
 You can verify that the restored database exists by querying the **Person.CountryRegion** table:
+
 ```sql
 USE AdventureWorksDW;
 SELECT * FROM Person.CountryRegion;
 ```
-  
+
 ## Install Python packages
 
 [Download and Install Azure Data Studio](../../azure-data-studio/download-azure-data-studio.md).
 
 Install the following Python packages:
-  * pyodbc
-  * pandas
+- `pyodbc`
+- `pandas`
+- `sqlalchemy`
+- `matplotlib`
 
-  To install these packages:
+To install these packages:
 
-  1. In your Azure Data Studio notebook, select **Manage Packages**.
-  2. In the **Manage Packages** pane, select the **Add new** tab.
-  3. For each of the following packages, enter the package name, click **Search**, then click **Install**.
+1. In your Azure Data Studio notebook, select **Manage Packages**.
+1. In the **Manage Packages** pane, select the **Add new** tab.
+1. For each of the following packages, enter the package name, select **Search**, then select **Install**.
 
 ## Plot histogram
 
-The distributed data displayed in the histogram is based on a SQL query from AdventureWorksDW. The histogram visualizes data and the frequency of data values. 
-Edit the connection string variables: 'server', 'database', 'username', and 'password' to connect to SQL database.
+The distributed data displayed in the histogram is based on a SQL query from `AdventureWorksDW`. The histogram visualizes data and the frequency of data values.
+
+Edit the connection string variables: 'server', 'database', 'username', and 'password' to connect to SQL Server database.
 
 To create a new notebook:
 
 1. In Azure Data Studio, select **File**, select **New Notebook**.
-2. In the notebook, select kernel **Python3**, select the **+code**.
-3. Paste code in notebook, select **Run All**.
+1. In the notebook, select kernel **Python3**, select the **+code**.
+1. Paste code in notebook, select **Run All**.
 
 ```python
 import pyodbc 
-import pandas as plt
+import pandas as pd
+import matplotlib
+import sqlalchemy
+
+from sqlalchemy import create_engine
+
+matplotlib.use('TkAgg', force=True)
+from matplotlib import pyplot as plt
+
 # Some other example server values are
 # server = 'localhost\sqlexpress' # for a named instance
 # server = 'myserver,port' # to specify an alternate port
-server = 'servername' 
-database = 'AdventureWorksDW' 
-username = 'yourusername' 
-password = 'databasename'  
-cnxn = pyodbc.connect('DRIVER={SQL Server};SERVER='+server+';DATABASE='+database+';UID='+username+';PWD='+ password)
-cursor = cnxn.cursor()
+server = 'servername'
+database = 'AdventureWorksDW2019'
+username = 'yourusername'
+password = 'databasename'
+
+url = 'mssql+pyodbc://{user}:{passwd}@{host}:{port}/{db}?driver=SQL+Server'.format(user=username, passwd=password, host=server, port=port, db=database)
+engine = create_engine(url)
+
 sql = "SELECT DATEDIFF(year, c.BirthDate, GETDATE()) AS Age FROM [dbo].[FactInternetSales] s INNER JOIN dbo.DimCustomer c ON s.CustomerKey = c.CustomerKey"
-df = plt.read_sql(sql, cnxn)
-df.hist(bins=10)
+
+df = pd.read_sql(sql, engine)
+df.hist(bins=50)
+
+plt.show()
 ```
 
-The display shows the age distribution of customers in the FactInternetSales table.
+The display shows the age distribution of customers in the `FactInternetSales` table.
 
-![Pandas Histogram](./media/python-histogram.png)
+:::image type="content" source="media/python-histogram.png" alt-text="Diagram showing the Pandas histogram distribution.":::