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

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

Connecting to Freshdesk Data

Connecting to Freshdesk 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.

FreshDesk makes use of basic authentication. To connect to data, set the following connection properties:

• Domain: Set this to the domain associated with your FreshDesk account. For example, in your URL: https://my_domain.freshdesk.com.
• APIKey: Set this to the API key associated with your FreshDesk account. To retrieve your API key, Log into your support Portal -> Click on profile picture in the top right corner -> profile settings page. The API key will be available below the change password section to the right.

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

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

engine = create_engine("freshdesk:///?Domain=MyDomain&APIKey=myAPIKey")

Execute SQL to Freshdesk

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 Tickets WHERE Status = '2'", engine)

Visualize Freshdesk Data

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

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

👁 Freshdesk data in a Python plot (Salesforce is shown).

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Freshdesk to start building Python apps and scripts with connectivity to Freshdesk 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("freshdesk:///?Domain=MyDomain&APIKey=myAPIKey")
df = pandas.read_sql("SELECT Id, Name FROM Tickets WHERE Status = '2'", engine)

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