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

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

Connecting to Printify Data

Connecting to Printify 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.

Start by setting the Profile connection property to the location of the Printify Profile on disk (e.g. C:\profiles\Profile.apip). Next, set the ProfileSettings connection property to the connection string for Printify (see below).

Printify API Profile Settings

In order to authenticate to Printify, you'll need to provide your API Key. To get your API Key navigate to My Profile, then Connections. In the Connections section you will be able to generate your Personal Access Token (API Key) and set your Token Access Scopes. Personal Access Tokens are valid for one year. An expired Personal Access Token can be re-generated using the same steps after it expires. Set the API Key to your Personal Access Token in the ProfileSettings property to connect.

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

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

engine = create_engine("api:///?Profile=C:\profiles\Printify.apip&ProfileSettings='APIKey=your_personal_token'")

Execute SQL to Printify

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, ShippingMethod FROM Tags WHERE Status = 'pending'", engine)

Visualize Printify Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to Printify 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("api:///?Profile=C:\profiles\Printify.apip&ProfileSettings='APIKey=your_personal_token'")
df = pandas.read_sql("SELECT Id, ShippingMethod FROM Tags WHERE Status = 'pending'", engine)

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