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Use pandas to Visualize SAP SuccessFactors Data in Python

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

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

Connecting to SAP SuccessFactors Data

Connecting to SAP SuccessFactors 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.

You can authenticate to SAP Success Factors using Basic authentication or OAuth with SAML assertion.

Basic Authentication

You must provide values for the following properties to successfully authenticate to SAP Success Factors. Note that the provider will reuse the session opened by SAP Success Factors using cookies. Which means that your credentials will be used only on the first request to open the session. After that, cookies returned from SAP Success Factors will be used for authentication.

  • Url: set this to the URL of the server hosting Success Factors. Some of the servers are listed in the SAP support documentation (external link).
  • User: set this to the username of your account.
  • Password: set this to the password of your account.
  • CompanyId: set this to the unique identifier of your company.

OAuth Authentication

You must provide values for the following properties, which will be used to get the access token.

  • Url: set this to the URL of the server hosting Success Factors. Some of the servers are listed in the SAP support documentation (external link).
  • User: set this to the username of your account.
  • CompanyId: set this to the unique identifier of your company.
  • OAuthClientId: set this to the API Key that was generated in API Center.
  • OAuthClientSecret: the X.509 private key used to sign SAML assertion. The private key can be found in the certificate you downloaded in Registering your OAuth Client Application.
  • InitiateOAuth: set this to GETANDREFRESH.

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

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

engine = create_engine("sapsuccessfactors:///?User=username&Password=password&CompanyId=CompanyId&Url=https://api4.successfactors.com")

Execute SQL to SAP SuccessFactors

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

df = pandas.read_sql("SELECT address1, zipCode FROM ExtAddressInfo WHERE city = 'Springfield'", engine)

Visualize SAP SuccessFactors Data

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

df.plot(kind="bar", x="address1", y="zipCode")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the SAP SuccessFactors Python Connector to start building Python apps and scripts with connectivity to SAP SuccessFactors 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("sapsuccessfactors:///?User=username&Password=password&CompanyId=CompanyId&Url=https://api4.successfactors.com")
df = pandas.read_sql("SELECT address1, zipCode FROM ExtAddressInfo WHERE city = 'Springfield'", engine)

df.plot(kind="bar", x="address1", y="zipCode")
plt.show()