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

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

Connecting to eBay Data

Connecting to eBay 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.

If you will be accessing your own account, you can generate an OAuthAccessToken from your developer account dashboard. You can also allow other users to securely access their own accounts.

Both of these methods require you to create an application key set to obtain values for the following connection properties: AppId, CertId, DevId, and SiteId.

The user consent flow additionally requires the RuName and CallbackURL.

See the "Getting Started" chapter in the help documentation for a guide to using OAuth.

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

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

engine = create_engine("ebay:///?AppId=MyAppId&CertId=MyCertId&DevId=MyDevId&SiteId=MySiteId&RuName=MyRuName&CallbackURL=http://localhost:33333&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to eBay

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

df = pandas.read_sql("SELECT Title, HitCount FROM ItemListing WHERE ListingStatus = 'active'", engine)

Visualize eBay Data

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

df.plot(kind="bar", x="Title", y="HitCount")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for eBay to start building Python apps and scripts with connectivity to eBay 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("ebay:///?AppId=MyAppId&CertId=MyCertId&DevId=MyDevId&SiteId=MySiteId&RuName=MyRuName&CallbackURL=http://localhost:33333&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT Title, HitCount FROM ItemListing WHERE ListingStatus = 'active'", engine)

df.plot(kind="bar", x="Title", y="HitCount")
plt.show()