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

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

Connecting to CockroachDB Data

Connecting to CockroachDB 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 to connect to CockroachDB.

• Server: The host name or IP address of the server.
• Port: The port number of the CockroachDB server. If not specified, the default port is 26257.
• Database: The name of the Cockroach database. If not specified, you connect to the user's default database.
• User: The Cockroach DB user account used to authenticate.
• Password: The password used to authenticate the user.

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

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

engine = create_engine("cockroachdb:///?User=root&Password=root&Database=system&Server=localhost&Port=26257")

Execute SQL to CockroachDB

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 CockroachDB Data

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

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

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for CockroachDB to start building Python apps and scripts with connectivity to CockroachDB 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("cockroachdb:///?User=root&Password=root&Database=system&Server=localhost&Port=26257")
df = pandas.read_sql("SELECT ShipName, ShipCity FROM Orders WHERE ShipCountry = 'USA'", engine)

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