Model Context Protocol (MCP) finally gives AI models a way to access the business data needed to make them really useful at work. CData MCP Servers have the depth and performance to make sure AI has access to all of the answers.
Try them now for free →How to Visualize IBM Informix Data in Python with pandas
Use pandas and other modules to analyze and visualize live IBM Informix 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 IBM Informix, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build IBM Informix-connected Python applications and scripts for visualizing IBM Informix data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to IBM Informix data, execute queries, and visualize the results.
With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live IBM Informix data in Python. When you issue complex SQL queries from IBM Informix, the driver pushes supported SQL operations, like filters and aggregations, directly to IBM Informix and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to IBM Informix Data
Connecting to IBM Informix 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.
Set the following properties to connect to IBM Informix
- Server: Set this to the name of the server running IBM Informix.
- Port: Set this to the port the IBM Informix server is listening on.
- Database: Set this to the name of the IBM Informix database.
- User: Set this to the username of a user allowed to access the database.
- Password: Set this to the password of a user allowed to access the database.
Follow the procedure below to install the required modules and start accessing IBM Informix 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 IBM Informix Data in Python
You can now connect with a connection string. Use the create_engine function to create an Engine for working with IBM Informix data.
engine = create_engine("informix:///?Server=10.0.1.2&Port=50000&User=admin&Password=admin&Database=test")
Execute SQL to IBM Informix
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, Price FROM Books WHERE Category = 'US'", engine)
Visualize IBM Informix Data
With the query results stored in a DataFrame, use the plot function to build a chart to display the IBM Informix data. The show method displays the chart in a new window.
df.plot(kind="bar", x="Id", y="Price") plt.show()

Free Trial & More Information
Download a free, 30-day trial of the CData Python Connector for IBM Informix to start building Python apps and scripts with connectivity to IBM Informix 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("informix:///?Server=10.0.1.2&Port=50000&User=admin&Password=admin&Database=test") df = pandas.read_sql("SELECT Id, Price FROM Books WHERE Category = 'US'", engine) df.plot(kind="bar", x="Id", y="Price") plt.show()