How to Visualize eBay Analytics 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 Analytics, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build eBay Analytics-connected Python applications and scripts for visualizing eBay Analytics data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to eBay Analytics 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 Analytics data in Python. When you issue complex SQL queries from eBay Analytics, the driver pushes supported SQL operations, like filters and aggregations, directly to eBay Analytics and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to eBay Analytics Data

Connecting to eBay Analytics 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.

You can authenticate to eBay Analytics only via the OAuth 2 authentication method. The eBay Analytics API requires an access token created with the authorization code grant flow to authorize the requests.

You can follow the guide in the Help documentation for a step by step guide on how to authenticate using the OAuth 2 protocol.

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

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

engine = create_engine("ebayanalytics:///?OAuthClientId=MyAppID&OAuthClientSecret=MyCertID&RuName=MyRuName&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to eBay Analytics

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

df = pandas.read_sql("SELECT ListingName, ClickThroughRate FROM TrafficReportByListing WHERE ListingId = '201284405428'", engine)

Visualize eBay Analytics Data

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

df.plot(kind="bar", x="ListingName", y="ClickThroughRate")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for eBay Analytics to start building Python apps and scripts with connectivity to eBay Analytics 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("ebayanalytics:///?OAuthClientId=MyAppID&OAuthClientSecret=MyCertID&RuName=MyRuName&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT ListingName, ClickThroughRate FROM TrafficReportByListing WHERE ListingId = '201284405428'", engine)

df.plot(kind="bar", x="ListingName", y="ClickThroughRate")
plt.show()