How to Visualize Customer.io 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 Customer.io-connected Python applications and scripts for visualizing Customer.io data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Customer.io data, execute queries, and visualize the results.

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

Connecting to Customer.io Data

Connecting to Customer.io 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.

Using API Key Authentication

To obtain your Customer.io App API Key, navigate to the Customer.io UI under Data & Integrations > Integrations > Customer.io API and generate your API key.

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Customer.io App API Key.

Example Connection String

Profile=C:\profiles\CustomerIO.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key";

Follow the procedure below to install the required modules and start accessing Customer.io 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 Customer.io Data in Python

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

engine = create_engine("api:///?Profile=C:\profiles\CustomerIO.apip&AuthScheme=APIKey&ProfileSettings="APIKey=your_api_key"")

Execute SQL to Customer.io

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

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

Visualize Customer.io Data

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

df.plot(kind="bar", x="", y="")
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 Customer.io 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\CustomerIO.apip&AuthScheme=APIKey&ProfileSettings="APIKey=your_api_key"")
df = pandas.read_sql("SELECT ,  FROM Customers WHERE  = ''", engine)

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