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Use pandas to Visualize Dynamics 365 Sales Data in Python

The CData Python Connector for Dynamics 365 Sales enables you use pandas and other modules to analyze and visualize live Dynamics 365 Sales 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 Dynamics 365 Sales, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Dynamics 365 Sales-connected Python applications and scripts for visualizing Dynamics 365 Sales data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Dynamics 365 Sales data, execute queries, and visualize the results.

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

Connecting to Dynamics 365 Sales Data

Connecting to Dynamics 365 Sales 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.

Dynamics 365 uses the OAuth authentication standard. See the Getting Started section in the help documentation for a guide to completing the process.

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

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

engine = create_engine("d365sales:///?OrganizationUrl=https://myaccount.crm.dynamics.com/&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to Dynamics 365 Sales

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

df = pandas.read_sql("SELECT accountid, Name FROM Accounts WHERE Name = 'MyAccount'", engine)

Visualize Dynamics 365 Sales Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the Dynamics 365 Sales Python Connector to start building Python apps and scripts with connectivity to Dynamics 365 Sales 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("d365sales:///?OrganizationUrl=https://myaccount.crm.dynamics.com/&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT accountid, Name FROM Accounts WHERE Name = 'MyAccount'", engine)

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