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

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

Connecting to Ontraport Data

Connecting to Ontraport 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 Ontraport Profile on disk (e.g. C:\profiles\Ontraport.apip). Next, set the ProfileSettings connection property to the connection string for Ontraport (see below).

Ontraport API Profile Settings

In your Ontraport account, navigate to Administration > Integrations > ONTRAPORT API Instructions and Key Manager to obtain both your API Key and App ID.

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

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

engine = create_engine("api:///?Profile=C:\profiles\Ontraport.apip&ProfileSettings='APIKey=your_api_key&AppId=your_app_id'")

Execute SQL to Ontraport

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 Deleted = 'false'", engine)

Visualize Ontraport Data

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

df.plot(kind="bar", x="Id", y="Name")
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 Ontraport 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\Ontraport.apip&ProfileSettings='APIKey=your_api_key&AppId=your_app_id'")
df = pandas.read_sql("SELECT Id, Name FROM Campaigns WHERE Deleted = 'false'", engine)

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