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

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

Connecting to Shopify Data

Connecting to Shopify 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 make use of all the features of the data provider, provide the AppId, Password, and ShopUrl connection properties.

To obtain these values, see the Getting Started section in the help documentation to register the data provider as an application with Shopify.

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

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

engine = create_engine("shopify:///?AppId=MyAppId&Password=MyPassword&ShopUrl=https://yourshopname.myshopify.com")

Execute SQL to Shopify

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

df = pandas.read_sql("SELECT FirstName, Id FROM Customers WHERE FirstName = 'jdoe1234'", engine)

Visualize Shopify Data

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

df.plot(kind="bar", x="FirstName", y="Id")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Shopify to start building Python apps and scripts with connectivity to Shopify 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("shopify:///?AppId=MyAppId&Password=MyPassword&ShopUrl=https://yourshopname.myshopify.com")
df = pandas.read_sql("SELECT FirstName, Id FROM Customers WHERE FirstName = 'jdoe1234'", engine)

df.plot(kind="bar", x="FirstName", y="Id")
plt.show()