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

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

Connecting to Klaviyo Data

Connecting to Klaviyo 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 authenticate to Klaviyo, provide an API Key. You can generate or view your API keys under 'My Account'

1. Navigate to 'Settings' > 'API Keys'
2. Click 'Create API Key'.
3. Name your API key and choose the desired scopes.

To connect in your CData solutions, set API Key to your Klaviyo API key.

If you wish to use OAuth authentication, refer to the Help documenation.

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

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

engine = create_engine("klaviyo:///?APIKey=my_api_key")

Execute SQL to Klaviyo

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, Name FROM Campaigns WHERE Status = 'draft'", engine)

Visualize Klaviyo Data

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

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

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Klaviyo to start building Python apps and scripts with connectivity to Klaviyo 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("klaviyo:///?APIKey=my_api_key")
df = pandas.read_sql("SELECT Id, Name FROM Campaigns WHERE Status = 'draft'", engine)

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