How to Visualize Salesforce Data 360 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 Data 360, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Salesforce Data 360-connected Python applications and scripts for visualizing Salesforce Data 360 data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Salesforce Data 360 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 360 data in Python. When you issue complex SQL queries from Salesforce Data 360, the driver pushes supported SQL operations, like filters and aggregations, directly to Salesforce Data 360 and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Salesforce Data 360 Data

Connecting to Salesforce Data 360 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 Data 360 supports authentication via the OAuth standard.

OAuth

Set AuthScheme to OAuth.

Desktop Applications

CData provides an embedded OAuth application that simplifies authentication at the desktop.

You can also authenticate from the desktop via a custom OAuth application, which you configure and register at the Salesforce Data 360 console. For further information, see Creating a Custom OAuth App in the Help documentation.

Before you connect, set these properties:

• InitiateOAuth: GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
• OAuthClientId (custom applications only): The Client ID assigned when you registered your custom OAuth application.
• OAuthClientSecret (custom applications only): The Client Secret assigned when you registered your custom OAuth application.

When you connect, the driver opens Salesforce Data 360's OAuth endpoint in your default browser. Log in and grant permissions to the application.

The driver then completes the OAuth process as follows:

• Extracts the access token from the callback URL.
• Obtains a new access token when the old one expires.
• Saves OAuth values in OAuthSettingsLocation so that they persist across connections.

For other OAuth methods, including Web Applications and Headless Machines, refer to the Help documentation.

Follow the procedure below to install the required modules and start accessing Salesforce Data 360 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 360 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 360 data.

engine = create_engine("salesforcedatacloud:///?InitiateOAuth=GETANDREFRESH")

Execute SQL to Salesforce Data 360

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

df = pandas.read_sql("SELECT [Account ID], [Account Name] FROM Account WHERE EmployeeCount = '250'", engine)

Visualize Salesforce Data 360 Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the Salesforce Data 360 data. The show method displays the chart in a new window.

df.plot(kind="bar", x="[Account ID]", y="[Account Name]")
plt.show()



Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Salesforce Data 360 to start building Python apps and scripts with connectivity to Salesforce Data 360 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("salesforcedatacloud:///?InitiateOAuth=GETANDREFRESH")
df = pandas.read_sql("SELECT [Account ID], [Account Name] FROM Account WHERE EmployeeCount = '250'", engine)

df.plot(kind="bar", x="[Account ID]", y="[Account Name]")
plt.show()