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

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

Connecting to Monday.com Data

Connecting to Monday.com 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 Monday.com using either API Token authentication or OAuth authentication.

Connecting with an API Token

Connect to Monday.com by specifying the APIToken. Set the AuthScheme to Token and obtain the APIToken as follows:

• API tokens for admin users
  1. Log in to your Monday.com account and click on your avatar in the bottom left corner.
  2. Select Admin.
  3. Select "API" on the left side of the Admin page.
  4. Click the "Copy" button to copy the user's API token.
• API tokens for non-admin users
  1. Click on your profile picture in the bottom left of your screen.
  2. Select "Developers"
  3. Click "Developer" and then "My Access Tokens" at the top.
  4. Select "Show" next to the API token, where you'll be able to copy it.

Connecting with OAuth Authentication

Alternatively, you can establish a connection using OAuth (refer to the OAuth section of the Help documentation).

Follow the procedure below to install the required modules and start accessing Monday.com 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 Monday.com Data in Python

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

engine = create_engine("monday:///?APIToken=eyJhbGciOiJIUzI1NiJ9.yJ0aWQiOjE0MTc4NzIxMiwidWlkIjoyNzI3ODM3OSwiaWFkIjoiMjAyMi0wMS0yMFQxMDo0NjoxMy45NDFaIiwicGV")

Execute SQL to Monday.com

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, DueDate FROM Invoices WHERE Status = 'SENT'", engine)

Visualize Monday.com Data

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

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

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Monday.com to start building Python apps and scripts with connectivity to Monday.com 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("monday:///?APIToken=eyJhbGciOiJIUzI1NiJ9.yJ0aWQiOjE0MTc4NzIxMiwidWlkIjoyNzI3ODM3OSwiaWFkIjoiMjAyMi0wMS0yMFQxMDo0NjoxMy45NDFaIiwicGV")
df = pandas.read_sql("SELECT Id, DueDate FROM Invoices WHERE Status = 'SENT'", engine)

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