Ready to get started?

Download a free trial of the SharePoint Excel Services Connector to get started:

 Download Now

Learn more:

SharePoint Excel Services Icon SharePoint Excel Services Python Connector

Python Connector Libraries for SharePoint Excel Services Data Connectivity. Integrate SharePoint Excel Services with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

Use pandas to Visualize SharePoint Excel Services Data in Python



The CData Python Connector for SharePoint Excel Services enables you use pandas and other modules to analyze and visualize live SharePoint Excel Services 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 SharePoint Excel Services, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build SharePoint Excel Services-connected Python applications and scripts for visualizing SharePoint Excel Services data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to SharePoint Excel Services data, execute queries, and visualize the results.

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

Connecting to SharePoint Excel Services Data

Connecting to SharePoint Excel Services 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.

The URL, User, and Password properties, under the Authentication section, must be set to valid credentials for SharePoint Online, SharePoint 2010, or SharePoint 2013. Additionally, the Library property must be set to a valid SharePoint Document Library and the File property must be set to a valid .xlsx file in the indicated Library.

Follow the procedure below to install the required modules and start accessing SharePoint Excel Services 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 SharePoint Excel Services Data in Python

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

engine = create_engine("excelservices:///?URL=https://myorg.sharepoint.com&User=admin@myorg.onmicrosoft.com&Password=password&File=Book1.xlsx")

Execute SQL to SharePoint Excel Services

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, AnnualRevenue FROM Account WHERE Industry = 'Floppy Disks'", engine)

Visualize SharePoint Excel Services Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the SharePoint Excel Services Python Connector to start building Python apps and scripts with connectivity to SharePoint Excel Services 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("excelservices:///?URL=https://myorg.sharepoint.com&User=admin@myorg.onmicrosoft.com&Password=password&File=Book1.xlsx")
df = pandas.read_sql("SELECT Name, AnnualRevenue FROM Account WHERE Industry = 'Floppy Disks'", engine)

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