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Use pandas to Visualize Google Campaign Manager Data in Python

The CData Python Connector for Google Campaign Manager enables you use pandas and other modules to analyze and visualize live Google Campaign Manager data in Python.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Google Campaign Manager, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Google Campaign Manager-connected Python applications and scripts for visualizing Google Campaign Manager data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Google Campaign Manager data, execute queries, and visualize the results.

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

Connecting to Google Campaign Manager Data

Connecting to Google Campaign Manager 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.

Google Campaign Manager uses the OAuth authentication standard. The data provider facilitates OAuth in various ways as described below. The following OAuth flow requires the authenticating user to interact with DoubleClick Campaign Manager, using the browser. You can also use a service account to authenticate.

For authentication guides, see the Getting Started section of the data provider help documentation.

Follow the procedure below to install the required modules and start accessing Google Campaign Manager 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 Google Campaign Manager Data in Python

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

engine = create_engine("googlecm:///?UserProfileID=MyUserProfileID&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to Google Campaign Manager

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

df = pandas.read_sql("SELECT Clicks, Device FROM CampaignPerformance WHERE Device = 'Mobile devices with full browsers'", engine)

Visualize Google Campaign Manager Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the Google Campaign Manager Python Connector to start building Python apps and scripts with connectivity to Google Campaign Manager 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("googlecm:///?UserProfileID=MyUserProfileID&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT Clicks, Device FROM CampaignPerformance WHERE Device = 'Mobile devices with full browsers'", engine)

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