How to Visualize BambooHR 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 BambooHR-connected Python applications and scripts for visualizing BambooHR data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to BambooHR data, execute queries, and visualize the results.

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

Connecting to BambooHR Data

Connecting to BambooHR 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 BambooHR Profile on disk (e.g. C:\profiles\bamboohr.apip). Next, set the ProfileSettings connection property to the connection string for BambooHR (see below).

BambooHR API Profile Settings

In order to authenticate to BambooHR, you'll need to provide your API Key. To generate an API key, log in and click your name in the upper right-hand corner of any page to get to the user context menu. If you have sufficient permissions, there will be an "API Keys" option in that menu to go to the page, where you can create a new API Key. Additionally, you will need to set the Domain, found in the domain name of your BambooHR account. For example if your BambooHR account is acmeinc.bamboohr.com, then the Domain should be 'acmeinc'. Set both the API Key and Domain in the ProfileSettings property to connect.

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

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

engine = create_engine("api:///?Profile=C:\profiles\BambooHR.apip&ProfileSettings='Domain=acmeinc&APIKey=your_api_key'")

Execute SQL to BambooHR

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

df = pandas.read_sql("SELECT Id, DisplayName FROM Employees WHERE Department = 'Sales'", engine)

Visualize BambooHR Data

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

df.plot(kind="bar", x="Id", y="DisplayName")
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 BambooHR 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\BambooHR.apip&ProfileSettings='Domain=acmeinc&APIKey=your_api_key'")
df = pandas.read_sql("SELECT Id, DisplayName FROM Employees WHERE Department = 'Sales'", engine)

df.plot(kind="bar", x="Id", y="DisplayName")
plt.show()