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

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

Connecting to LinkedIn Ads Data

Connecting to LinkedIn Ads 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.

LinkedIn Ads uses the OAuth authentication standard. OAuth requires the authenticating user to interact with LinkedIn using the browser. See the OAuth section in the Help documentation for a guide.

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

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

engine = create_engine("linkedinads:///?OAuthClientId=MyOAuthClientId&OAuthClientSecret=MyOAuthClientSecret&CallbackURL=http://localhost:portNumber&InitiateOAuth=GETANDREFRESH")

Execute SQL to LinkedIn Ads

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

df = pandas.read_sql("SELECT VisibilityCode, Comment FROM Analytics WHERE EntityId = '238'", engine)

Visualize LinkedIn Ads Data

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

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

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for LinkedIn Ads to start building Python apps and scripts with connectivity to LinkedIn Ads 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("linkedinads:///?OAuthClientId=MyOAuthClientId&OAuthClientSecret=MyOAuthClientSecret&CallbackURL=http://localhost:portNumber&InitiateOAuth=GETANDREFRESH")
df = pandas.read_sql("SELECT VisibilityCode, Comment FROM Analytics WHERE EntityId = '238'", engine)

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