How to Visualize Office 365 Data in Python with pandas

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Office 365, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Office 365-connected Python applications and scripts for visualizing Office 365 data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Office 365 data, execute queries, and visualize the results.

With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Office 365 data in Python. When you issue complex SQL queries from Office 365, the driver pushes supported SQL operations, like filters and aggregations, directly to Office 365 and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Office 365 Data

Connecting to Office 365 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.

Office 365 uses the OAuth authentication standard. To authenticate requests, you will need to obtain the OAuthClientId, OAuthClientSecret, and OAuthCallbackURL by registering an app with Office 365. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

Follow the procedure below to install the required modules and start accessing Office 365 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 Office 365 Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Office 365 data.

engine = create_engine("office365:///?OAuthClientId=MyApplicationId&OAuthClientSecret=MyAppKey&OAuthCallbackURL=http://localhost:33333&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to Office 365

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

df = pandas.read_sql("SELECT Name, Size FROM Files WHERE UserId = '54f34750-0d34-47c9-9949-9fac4791cddb'", engine)

Visualize Office 365 Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the Office 365 data. The show method displays the chart in a new window.

df.plot(kind="bar", x="Name", y="Size")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Office 365 to start building Python apps and scripts with connectivity to Office 365 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("office365:///?OAuthClientId=MyApplicationId&OAuthClientSecret=MyAppKey&OAuthCallbackURL=http://localhost:33333&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT Name, Size FROM Files WHERE UserId = '54f34750-0d34-47c9-9949-9fac4791cddb'", engine)

df.plot(kind="bar", x="Name", y="Size")
plt.show()