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

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

Connecting to Amazon Marketplace Data

Connecting to Amazon Marketplace 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.

To connect to the Amazon Marketplace Webservice (MWS), AWSAccessKeyId, MWSAuthToken, AWSSecretKey and SellerId are required. You can optionally set the Marketplace property. For more information on obtaining values for these properties, refer to the Help documentation.

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

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

engine = create_engine("amazonmarketplace:///?AWS Access Key Id=myAWSAccessKeyId&AWS Secret Key=myAWSSecretKey&MWS Auth Token=myMWSAuthToken&Seller Id=mySellerId&Marketplace=United States")

Execute SQL to Amazon Marketplace

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

df = pandas.read_sql("SELECT AmazonOrderId, OrderStatus FROM Orders WHERE IsReplacementOrder = 'True'", engine)

Visualize Amazon Marketplace Data

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

df.plot(kind="bar", x="AmazonOrderId", y="OrderStatus")
plt.show()

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Amazon Marketplace to start building Python apps and scripts with connectivity to Amazon Marketplace 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("amazonmarketplace:///?AWS Access Key Id=myAWSAccessKeyId&AWS Secret Key=myAWSSecretKey&MWS Auth Token=myMWSAuthToken&Seller Id=mySellerId&Marketplace=United States")
df = pandas.read_sql("SELECT AmazonOrderId, OrderStatus FROM Orders WHERE IsReplacementOrder = 'True'", engine)

df.plot(kind="bar", x="AmazonOrderId", y="OrderStatus")
plt.show()