How to Visualize Salesforce CRM Analytics 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 Salesforce CRM Analytics, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Salesforce CRM Analytics-connected Python applications and scripts for visualizing Salesforce CRM Analytics data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Salesforce CRM Analytics data, execute queries, and visualize the results.

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

Connecting to Salesforce CRM Analytics Data

Connecting to Salesforce CRM Analytics 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.

Salesforce CRM Analytics uses the OAuth 2 authentication standard. Obtain the OAuthClientId and OAuthClientSecret by registering an app with Salesforce CRM Analytics.

See the Getting Started section of the Help documentation for an authentication guide.

Multi-Factor Authentication (MFA)

If the connected Salesforce org has MFA enforcement enabled, set MFACode to the time-based one-time passcode (TOTP) generated by your authenticator app (such as Salesforce Authenticator or Google Authenticator). MFACode applies alongside the standard OAuth flow.

Follow the procedure below to install the required modules and start accessing Salesforce CRM Analytics 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 Salesforce CRM Analytics Data in Python

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

engine = create_engine("salesforcecrmanalytics:///?OAuthClientId=MyConsumerKey&OAuthClientSecret=MyConsumerSecret&CallbackURL=http://localhost:portNumber&InitiateOAuth=GETANDREFRESH&MFACode=YourMFACode")

Execute SQL to Salesforce CRM Analytics

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, CloseDate FROM Dataset_Opportunity WHERE StageName = 'Closed Won'", engine)

Visualize Salesforce CRM Analytics Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Salesforce CRM Analytics to start building Python apps and scripts with connectivity to Salesforce CRM Analytics 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("salesforcecrmanalytics:///?OAuthClientId=MyConsumerKey&OAuthClientSecret=MyConsumerSecret&CallbackURL=http://localhost:portNumber&InitiateOAuth=GETANDREFRESH&MFACode=YourMFACode")
df = pandas.read_sql("SELECT Name, CloseDate FROM Dataset_Opportunity WHERE StageName = 'Closed Won'", engine)

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