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

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

Connecting to Google Calendar Data

Connecting to Google Calendar 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.

You can connect to Google APIs on behalf of individual users or on behalf of a domain. Google uses the OAuth authentication standard. See the "Getting Started" section of the help documentation for a guide.

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

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

engine = create_engine("googlecalendar:///?")

Execute SQL to Google Calendar

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

df = pandas.read_sql("SELECT Summary, StartDateTime FROM VacationCalendar WHERE SearchTerms = 'beach trip'", engine)

Visualize Google Calendar Data

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

df.plot(kind="bar", x="Summary", y="StartDateTime")
plt.show()

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Google Calendars to start building Python apps and scripts with connectivity to Google Calendar 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("googlecalendar:///?")
df = pandas.read_sql("SELECT Summary, StartDateTime FROM VacationCalendar WHERE SearchTerms = 'beach trip'", engine)

df.plot(kind="bar", x="Summary", y="StartDateTime")
plt.show()