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

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

Connecting to CouchDB Data

Connecting to CouchDB 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:

• Url: The Url of your instance. For example: http://localhost:5984
• User The Apache CouchDB user account used to authenticate.
• Password The Apache CouchDB password associated with the authenticating user.

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

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

engine = create_engine("apachecouchdb:///?Url=http://localhost:5984&User=abc123&Password=abcdef")

Execute SQL to CouchDB

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

df = pandas.read_sql("SELECT MovieRuntime, MovieRating FROM Movies WHERE MovieRating = 'R'", engine)

Visualize CouchDB Data

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

df.plot(kind="bar", x="MovieRuntime", y="MovieRating")
plt.show()

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for CouchDB to start building Python apps and scripts with connectivity to CouchDB 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("apachecouchdb:///?Url=http://localhost:5984&User=abc123&Password=abcdef")
df = pandas.read_sql("SELECT MovieRuntime, MovieRating FROM Movies WHERE MovieRating = 'R'", engine)

df.plot(kind="bar", x="MovieRuntime", y="MovieRating")
plt.show()