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

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

Connecting to UKG Pro HCM Data

Connecting to UKG Pro HCM 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.

Start by setting the Profile connection property to the location of the UKGProHCM Profile on disk (e.g. C:\profiles\UKGProHCM.apip). Next, set the ProfileSettings connection property to the connection string for UKGProHCM (see below).

UKGProHCM API Profile Settings

UKG Pro HCM uses Basic authentication combined with a customer API key to authorize access to the API. To connect, you will need your UKG Pro HCM credentials and a customer API key issued by UKG.

Set the following connection properties to authenticate:

• AuthScheme: Set this to Basic.
• User: Set this to your UKG Pro HCM username.
• Password: Set this to your UKG Pro HCM password.
• ProfileSettings: Set this to a semicolon-separated list containing:
  • Host: Your UKG Pro HCM tenant hostname (e.g., yourcompany.ultipro.com).
  • CustomerAPIKey: Your UKG customer API key. This is passed as the US-CUSTOMER-API-KEY request header on each API call.

To obtain your customer API key, contact your UKG Pro HCM administrator or refer to the UKG Developer Portal at https://developer.ukg.com.

Follow the procedure below to install the required modules and start accessing UKG Pro HCM 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 UKG Pro HCM Data in Python

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

engine = create_engine("api:///?Profile=C:\profiles\UKGProHCM.apip&AuthScheme=Basic&User=your_username&Password=your_password&ProfileSettings='Host=yourcompany.ultipro.com&CustomerAPIKey=your_customer_api_key'")

Execute SQL to UKG Pro HCM

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

df = pandas.read_sql("SELECT UserId, UserName FROM UserDetails WHERE UserStatus = 'A'", engine)

Visualize UKG Pro HCM Data

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

df.plot(kind="bar", x="UserId", y="UserName")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to UKG Pro HCM 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("api:///?Profile=C:\profiles\UKGProHCM.apip&AuthScheme=Basic&User=your_username&Password=your_password&ProfileSettings='Host=yourcompany.ultipro.com&CustomerAPIKey=your_customer_api_key'")
df = pandas.read_sql("SELECT UserId, UserName FROM UserDetails WHERE UserStatus = 'A'", engine)

df.plot(kind="bar", x="UserId", y="UserName")
plt.show()