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Use pandas to Visualize RSS Feeds in Python

The CData Python Connector for RSS enables you use pandas and other modules to analyze and visualize live RSS feeds 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 RSS, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build RSS-connected Python applications and scripts for visualizing RSS feeds. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to RSS feeds, execute queries, and visualize the results.

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

Connecting to RSS Feeds

Connecting to RSS feeds 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 RSS and Atom feeds, as well as feeds with custom extensions. To connect to a feed, set the URL property. You can also access secure feeds. A variety of authentication mechanisms are supported. See the help documentation for details.

Follow the procedure below to install the required modules and start accessing RSS 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 RSS Feeds in Python

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

engine = create_engine("rss:///?URL=http://broadcastCorp/rss/")

Execute SQL to RSS

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

df = pandas.read_sql("SELECT Author, Pubdate FROM Latest News WHERE Category = 'US'", engine)

Visualize RSS Feeds

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

df.plot(kind="bar", x="Author", y="Pubdate")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the RSS Python Connector to start building Python apps and scripts with connectivity to RSS feeds. 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("rss:///?URL=http://broadcastCorp/rss/")
df = pandas.read_sql("SELECT Author, Pubdate FROM Latest News WHERE Category = 'US'", engine)

df.plot(kind="bar", x="Author", y="Pubdate")
plt.show()