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

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

Connecting to MariaDB Data

Connecting to MariaDB 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.

The Server and Port properties must be set to a MariaDB server. If IntegratedSecurity is set to false, then User and Password must be set to valid user credentials. Optionally, Database can be set to connect to a specific database. If not set, the tables from all databases are reported.

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

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

engine = create_engine("mariadb:///?User=myUser&Password=myPassword&Database=NorthWind&Server=myServer&Port=3306")

Execute SQL to MariaDB

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

df = pandas.read_sql("SELECT ShipName, ShipCity FROM Orders WHERE ShipCountry = 'USA'", engine)

Visualize MariaDB Data

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

df.plot(kind="bar", x="ShipName", y="ShipCity")
plt.show()

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for MariaDB to start building Python apps and scripts with connectivity to MariaDB 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("mariadb:///?User=myUser&Password=myPassword&Database=NorthWind&Server=myServer&Port=3306")
df = pandas.read_sql("SELECT ShipName, ShipCity FROM Orders WHERE ShipCountry = 'USA'", engine)

df.plot(kind="bar", x="ShipName", y="ShipCity")
plt.show()