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

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

Connecting to Adobe Target Data

Connecting to Adobe Target 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 connect to Adobe Target, you must provide the Tenant property along with OAuth connection properties mentioned below. Note that while other connection properties can influence processing behavior, they do not affect the ability to connect.

To determine your Tenant name:

1. Log in to Adobe Experience. The URL will look similar to: "https://experience.adobe.com/#/@mycompanyname/preferences/general-section".
2. Extract the value after the "/#/@". In this example, it is "mycompanyname".
3. Set the Tenant connection property to that value.

User Accounts (OAuth)

You must set AuthScheme to OAuthClient for all user account flows.

Note: Adobe authentication via OAuth requires updating your token every two weeks.

All Applications

Obtaining the OAuth Access Token

Set the following properties to connect:

• InitiateOAuth: Set to GETANDREFRESH to automatically perform the OAuth exchange and refresh the OAuthAccessToken as needed.
• OAuthClientId : Set to the client Id assigned when you registered your app.
• OAuthClientSecret : Set to the client secret assigned when you registered your app.
• CallbackURL : Set to the redirect URI defined when you registered your app. For example: https://localhost:3333

With these settings, the provider obtains an access token from Adobe Target, which it uses to request data. The OAuth values are stored in the location specified by OAuthSettingsLocation, ensuring they persist across connections.

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

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

engine = create_engine("adobetarget:///?Tenant=mycompanyname&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to Adobe Target

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 Activities WHERE Type = 'AB'", engine)

Visualize Adobe Target Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the Adobe Target 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 Python Connector for Adobe Target to start building Python apps and scripts with connectivity to Adobe Target 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("adobetarget:///?Tenant=mycompanyname&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT Id, Name FROM Activities WHERE Type = 'AB'", engine)

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