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

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

Connecting to Rebilly Data

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

Rebilly API Profile Settings

Generate an API Key in Rebilly by navigating to Automations > Integrations > Custom Integrations > API Keys and selecting Secret as the type.

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

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

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

Execute SQL to Rebilly

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, Name FROM Attachments WHERE RelatedType = 'customer'", engine)

Visualize Rebilly Data

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

df.plot(kind="bar", x="Id", y="Name")
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 Rebilly 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\Rebilly.apip&ProfileSettings='APIKey=your_api_key'")
df = pandas.read_sql("SELECT Id, Name FROM Attachments WHERE RelatedType = 'customer'", engine)

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