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Python Connector Libraries for ShipStation Data Connectivity. Integrate ShipStation with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

How to Visualize ShipStation Data in Python with pandas

Use pandas and other modules to analyze and visualize live ShipStation data in Python.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for ShipStation, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build ShipStation-connected Python applications and scripts for visualizing ShipStation data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to ShipStation data, execute queries, and visualize the results.

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

Connecting to ShipStation Data

Connecting to ShipStation 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.

Use the BASIC Authentication standard to connect.

  1. Login to your ShipStation account
  2. Click on the settings icon in the upper right corner. A column menu will show up on the left
  3. Click Account -> API Settings
  4. On the API Settings page, note the API Key and API Secret.

Authenticating to ShipStation

  • APIKey: Set this to the API key from the API settings page.
  • APISecret: Set this to the Secret key from the API settings page.

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

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

engine = create_engine("shipstation:///?APIKey='YourAPIKey'&APISecret='YourAPISecret'")

Execute SQL to ShipStation

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, Color FROM Tags WHERE CustomerId = '1368175'", engine)

Visualize ShipStation Data

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

df.plot(kind="bar", x="Id", y="Color")

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for ShipStation to start building Python apps and scripts with connectivity to ShipStation 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("shipstation:///?APIKey='YourAPIKey'&APISecret='YourAPISecret'")
df = pandas.read_sql("SELECT Id, Color FROM Tags WHERE CustomerId = '1368175'", engine)

df.plot(kind="bar", x="Id", y="Color")