Use pandas to Visualize EDGAR Online Data in Python

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EDGAR Online Python Connector

Python Connector Libraries for EDGAR Online Data Connectivity. Integrate EDGAR Online with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

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

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

Connecting to EDGAR Online Data

Connecting to EDGAR Online 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.

  1. Navigate to and create an account.
  2. Register a new application and retrieve the AppKey. You should select one of the available Web APIs this application will use like HackPack, Insider Trades or Institutional Ownership.
    Note: HackPack is the most important Web API that an application can use since it supports a large number of endpoints. If you are getting the "Access Denied" error you must create a new app and select the correct Web API which supports the resource you are querying.
  3. After successfully creating a new app, you can access your keys through your "my account" area. Set the AppKey connection property value equal to the Key of your application.

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

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

engine = create_engine("edgaronline:///?AppKey=20dd8ce9904d422ed89ebde1ad40d")

Execute SQL to EDGAR Online

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, Name FROM Subscriptions WHERE SubscriberEmail = ''", engine)

Visualize EDGAR Online Data

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

df.plot(kind="bar", x="Id", y="Name")

Free Trial & More Information

Download a free, 30-day trial of the EDGAR Online Python Connector to start building Python apps and scripts with connectivity to EDGAR Online 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("edgaronline:///?AppKey=20dd8ce9904d422ed89ebde1ad40d")
df = pandas.read_sql("SELECT Id, Name FROM Subscriptions WHERE SubscriberEmail = ''", engine)

df.plot(kind="bar", x="Id", y="Name")