How to Visualize Salesforce 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, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Salesforce-connected Python applications and scripts for visualizing Salesforce data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Salesforce 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 data in Python. When you issue complex SQL queries from Salesforce, the driver pushes supported SQL operations, like filters and aggregations, directly to Salesforce and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Getting Started

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Connecting to Salesforce Data

Connecting to Salesforce 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.

There are several authentication methods available for connecting to Salesforce: OAuth, Login (or basic), and SSO. The Login method requires you to have the username, password, and security token of the user.

OAuth Authentication (default)

The default authentication mechanism (and the one preferred by Salesforce) is OAuth. To use OAuth with CData's embedded OAuth application, leave the connection properties blank. If you have configured your own custom OAuth application with Salesforce (see the Help documentation for more information), set OAuthClientId, OAuthClientSecret, and CallbackURL to the properties for you application. Set InitiateOAuth to the desired OAuth flow ("GETANDREFRESH" will have the connector manage the entire OAuth flow).

Login (or Basic) Authentication

If you do not wish do not wish to use OAuth authentication, you can use Login (or basic) authentication. Set AuthScheme to Basic, and set the User, Password, and SecurityToken properties. You can configure your security token in Salesforce.

SSO (single sign-on) Authentication

SSO (single sign-on) can be used by setting the SSOProperties, SSOLoginUrl, and SSOExchangeURL connection properties, which allow you to authenticate to an identity provider. See the "Getting Started" chapter in the Help documentation for more information.

Multi-Factor Authentication (MFA)

If your 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 to both OAuth and Login authentication flows.

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

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

engine = create_engine("salesforce:///?InitiateOAuth=GETANDREFRESH&MFACode=YourMFACode")

Execute SQL to Salesforce

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

df = pandas.read_sql("SELECT Industry, AnnualRevenue FROM Account WHERE Name = 'GenePoint'", engine)

Visualize Salesforce Data

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

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

👁 Salesforce data in a Python plot (Salesforce is shown).

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Salesforce to start building Python apps and scripts with connectivity to Salesforce data. Reach out to our Support Team if you have any questions.

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Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("salesforce:///?InitiateOAuth=GETANDREFRESH&MFACode=YourMFACode")
df = pandas.read_sql("SELECT Industry, AnnualRevenue FROM Account WHERE Name = 'GenePoint'", engine)

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