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How to Visualize Calendly Data in Python with pandas

Use pandas and other modules to analyze and visualize live Calendly data in Python.

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

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

Connecting to Calendly Data

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

Calendly API Profile Settings

To authenticate to Calendly, you will need to provide an API Key. The Calendly API Key, can be found in your Calendly account, under 'Integrations' > 'API & Webhooks' > 'Generate New Token'. Set the APIKey in the ProfileSettings connection property.

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

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

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

Execute SQL to Calendly

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

df = pandas.read_sql("SELECT Uri, Name FROM OrganizationScheduledEvents WHERE EventType = 'Meeting'", engine)

Visualize Calendly Data

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

df.plot(kind="bar", x="Uri", y="Name")

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 Calendly 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\Calendly.apip&ProfileSettings='APIKey=your_api_token'")
df = pandas.read_sql("SELECT Uri, Name FROM OrganizationScheduledEvents WHERE EventType = 'Meeting'", engine)

df.plot(kind="bar", x="Uri", y="Name")