Ready to get started?

Learn more about the CData Python Connector for Azure Management or download a free trial:

Download Now

Use pandas to Visualize Azure Management Data in Python

The CData Python Connector for Azure Management enables you use pandas and other modules to analyze and visualize live Azure Management data in Python.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Azure Management, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Azure Management-connected Python applications and scripts for visualizing Azure Management data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Azure Management data, execute queries, and visualize the results.

With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Azure Management data in Python. When you issue complex SQL queries from Azure Management, the driver pushes supported SQL operations, like filters and aggregations, directly to Azure Management and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Azure Management Data

Connecting to Azure Management data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

Azure Data Management uses the OAuth 2 authentication standard. See the Getting Started section of the CData driver documentation for a guide.

Follow the procedure below to install the required modules and start accessing Azure Management through Python objects.

Install Required Modules

Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:

pip install pandas
pip install matplotlib
pip install sqlalchemy

Be sure to import the module with the following:

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engine

Visualize Azure Management Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Azure Management data.

engine = create_engine("azuredatamanagement:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to Azure Management

Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.

df = pandas.read_sql("SELECT DisplayName, AuthorizationSource FROM Subscriptions WHERE SubscriptionId = 'fadc4-4cdaf-fadc4-4cdaf'", engine)

Visualize Azure Management Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the Azure Management data. The show method displays the chart in a new window.

df.plot(kind="bar", x="DisplayName", y="AuthorizationSource")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the Azure Management Python Connector to start building Python apps and scripts with connectivity to Azure Management data. Reach out to our Support Team if you have any questions.



Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("azuredatamanagement:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT DisplayName, AuthorizationSource FROM Subscriptions WHERE SubscriptionId = 'fadc4-4cdaf-fadc4-4cdaf'", engine)

df.plot(kind="bar", x="DisplayName", y="AuthorizationSource")
plt.show()