Use pandas to Visualize Excel Online Data in Python

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Excel Online Python Connector

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



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

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

Connecting to Excel Online Data

Connecting to Excel Online 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.

You can connect to a workbook by providing authentication to Excel Online and then setting the following properties:

  • Workbook: Set this to the name or Id of the workbook.

    If you want to view a list of information about the available workbooks, execute a query to the Workbooks view after you authenticate.

  • UseSandbox: Set this to true if you are connecting to a workbook in a sandbox account. Otherwise, leave this blank to connect to a production account.

You use the OAuth authentication standard to authenticate to Excel Online. See the Getting Started section in the help documentation for a guide. Getting Started also guides you through executing SQL to worksheets and ranges.

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

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

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

Execute SQL to Excel Online

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

df = pandas.read_sql("SELECT Id, Column1 FROM Test_xlsx_Sheet1 WHERE Column2 = 'Bob'", engine)

Visualize Excel Online Data

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

df.plot(kind="bar", x="Id", y="Column1")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the Excel Online Python Connector to start building Python apps and scripts with connectivity to Excel Online 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("excelonline:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT Id, Column1 FROM Test_xlsx_Sheet1 WHERE Column2 = 'Bob'", engine)

df.plot(kind="bar", x="Id", y="Column1")
plt.show()