---
title: Plot a histogram for data exploration with Python
titleSuffix: SQL machine learning
description: Learn how to create a histogram to visualize data using Python.
author: WilliamDAssafMSFT
ms.author: wiassaf
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

[!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

::: 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)
::: moniker-end

::: moniker range="=azuresqldb-current"
- [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)

- [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).

- [Restore sample DW database](../../samples/adventureworks-install-configure.md) to get sample data used in this article.

## 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`
- `sqlalchemy`
- `matplotlib`

To install these packages:

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 [!INCLUDE [sssampledbdwobject-md](../../includes/sssampledbdwobject-md.md)]. 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**.
1. In the notebook, select kernel **Python3**, select the **+code**.
1. Paste code in notebook, select **Run All**.

```python
import pyodbc 
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 = 'AdventureWorksDW2022'
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 = pd.read_sql(sql, engine)
df.hist(bins=50)

plt.show()
```

The display shows the age distribution of customers in the `FactInternetSales` table.

:::image type="content" source="media/python-histogram.png" alt-text="Diagram showing the Pandas histogram distribution.":::