Use pandas to Visualize Trello Data in Python

Ready to get started?

Download for a free trial:

Download Now

Learn more:

Trello Python Connector

Python Connector Libraries for Trello Data Connectivity. Integrate Trello with popular Python tools like Pandas, SQLAlchemy, Dash & petl.



The CData Python Connector for Trello enables you use pandas and other modules to analyze and visualize live Trello data in Python.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Trello, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Trello-connected Python applications and scripts for visualizing Trello data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Trello data, execute queries, and visualize the results.

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

Connecting to Trello Data

Connecting to Trello 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.

Trello uses token-based authentication to grant third-party applications access to their API. When a user has granted an application access to their data, the application is given a token that can be used to make requests to Trello's API.

Trello's API can be accessed in 2 different ways. The first is using Trello's own Authorization Route, and the second is using OAuth1.0.

  • Authorization Route: At the moment of registration, Trello assigns an API key and Token to the account. See the Help documentation for information on how to connect via the Authorization route.
  • OAuth Route: Similar to using Authorization, OAuth creates an Application Id and Secret when you create your account. See the Help documentation for information on how to to connect.

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

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

engine = create_engine("trello:///?APIKey=myApiKey&Token=myGeneratedToken&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to Trello

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

df = pandas.read_sql("SELECT BoardId, Name FROM Boards WHERE Name = 'Public Board'", engine)

Visualize Trello Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the Trello Python Connector to start building Python apps and scripts with connectivity to Trello 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("trello:///?APIKey=myApiKey&Token=myGeneratedToken&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT BoardId, Name FROM Boards WHERE Name = 'Public Board'", engine)

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