How to Visualize Dynamics CRM Data in Python with pandas via CData Connect AI
The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Connect AI Python SDK, the pandas and Matplotlib modules, you can build Dynamics CRM-connected Python applications and scripts for visualizing Dynamics CRM data. This article shows how to connect to Connect AI and use the pandas and Matplotlib built-in functions to query Dynamics CRM data and visualize the results.
The Connect AI Python SDK (cdata-connect-ai) is a DB-API 2.0 (PEP 249) compliant client, so pandas can read query results directly from the SDK connection object. There is no driver to install per source and no SQLAlchemy engine to configure: connect with a Personal Access Token and pass the connection straight to pandas.read_sql.
About Dynamics CRM Data Integration
CData simplifies access and integration of live Microsoft Dynamics CRM data. Our customers leverage CData connectivity to:
- Read and write data in the Dynamics CRM 2011+ Services and Dynamics CRM Online.
- Extend the native features of Dynamics CRM with customizable caching and intelligent query aggregation and separation.
- Authenticate securely with Dynamics CRM in a variety of ways, including Microsoft Entra ID, Azure Managed Service Identity credentials, and Azure Service Principal using either a client secret or a certificate.
CData customers use our Dynamics CRM connectivity solutions for a variety of reasons, whether they're looking to replicate their data into a data warehouse (alongside other data sources) or analyze live Dynamics CRMa data from their preferred data tools inside the Microsoft ecosystem (Power BI, Excel, etc.) or with external tools (Tableau, Looker, etc.).
Getting Started
Connect to Dynamics CRM in Connect AI
CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.
- Log into Connect AI, click Sources, and then click Add Connection
- Select "Dynamics CRM" from the Add Connection panel
-
Enter the necessary authentication properties to connect to Dynamics CRM.
The connection string options meet the authentication and connection requirements of different Dynamics CRM instances. To connect to your instance, set the User and Password properties, under the Authentication section, to valid Dynamics CRM user credentials and set the Url to a valid Dynamics CRM server organization root. Additionally, set the CRMVersion property to 'CRM2011+' or 'CRMOnline'. IFD configurations are supported as well; set InternetFacingDeployment to true.
Additionally, you can provide the security token service (STS) or AD FS endpoint in the STSURL property. This value can be retrieved with the GetSTSUrl stored procedure. Office 365 users can connect to the default STS URL by simply setting CRMVersion.
- Click Save & Test
- Navigate to the Permissions tab and update the user-based permissions.
Generate a Personal Access Token (PAT)
The Python SDK authenticates to Connect AI with your account email and a Personal Access Token (PAT). It is best practice to create a separate PAT for each application to maintain granularity of access.
- Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
- Give the PAT a name and click Create.
- The PAT is only visible at creation, so copy it and store it securely.
Install Required Modules
Install the SDK (with the pandas extra) and Matplotlib using the pip utility:
pip install "cdata-connect-ai[full]" pip install matplotlib
Visualize Dynamics CRM Data in Python
Import the modules, then connect to Connect AI with your account email and PAT. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, DynamicsCRM1).
import pandas
import matplotlib.pyplot as plt
import cdata_connect_ai
conn = cdata_connect_ai.connect(
username="[email protected]",
password="<your_pat>",
)
Query Dynamics CRM with pandas
Use the read_sql function from pandas to execute a SQL statement and store the result set in a DataFrame. Pass the SDK connection directly, no engine required.
df = pandas.read_sql(
"SELECT FirstName, NumberOfEmployees "
"FROM [DynamicsCRM1].[DynamicsCRM].[Account] "
"WHERE FirstName = 'Bob'",
conn,
)
Note: pandas may print a UserWarning stating that it only officially supports SQLAlchemy connectables. This is expected when passing a DB-API connection directly—the query runs correctly and the warning is safe to ignore.
Visualize Dynamics CRM Data
With the query results stored in a DataFrame, use the plot function to build a chart. The show method displays the chart in a new window.
df.plot(kind="bar", x="FirstName", y="NumberOfEmployees") plt.show() conn.close()
More Information and Free Trial
Now you can read live Dynamics CRM data into pandas through the CData Connect AI Python SDK. For more information on connecting to Dynamics CRM (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start working with live Dynamics CRM data in Python.
Full Source Code
import pandas
import matplotlib.pyplot as plt
import cdata_connect_ai
conn = cdata_connect_ai.connect(
username="[email protected]",
password="<your_pat>",
)
df = pandas.read_sql(
"SELECT FirstName, NumberOfEmployees "
"FROM [DynamicsCRM1].[DynamicsCRM].[Account] "
"WHERE FirstName = 'Bob'",
conn,
)
df.plot(kind="bar", x="FirstName", y="NumberOfEmployees")
plt.show()
conn.close()