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Get the Report →How to Visualize Bing Ads Data in Python with pandas
Use pandas and other modules to analyze and visualize live Bing Ads 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 Bing Ads, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Bing Ads-connected Python applications and scripts for visualizing Bing Ads data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Bing 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 Bing Ads data in Python. When you issue complex SQL queries from Bing Ads, the driver pushes supported SQL operations, like filters and aggregations, directly to Bing Ads and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Bing Ads Data
Connecting to Bing 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.
The Bing Ads APIs use the OAuth 2 standard. To authenticate, you will need valid Bing Ads OAuth credentials and you will need to obtain a developer token. See the Getting Started section in the Bing Ads data provider help documentation for an authentication guide.
Follow the procedure below to install the required modules and start accessing Bing 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 Bing Ads Data in Python
You can now connect with a connection string. Use the create_engine function to create an Engine for working with Bing Ads data.
engine = create_engine("bingads:///? OAuthClientId=MyOAuthClientId& OAuthClientSecret=MyOAuthClientSecret& CallbackURL=http://localhost:portNumber& AccountId=442311& CustomerId=5521444& DeveloperToken=11112332233&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
Execute SQL to Bing 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 Id, Name FROM AdGroups WHERE CampaignId = '234505536'", engine)
Visualize Bing Ads Data
With the query results stored in a DataFrame, use the plot function to build a chart to display the Bing Ads 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 Bing Ads to start building Python apps and scripts with connectivity to Bing Ads 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("bingads:///? OAuthClientId=MyOAuthClientId& OAuthClientSecret=MyOAuthClientSecret& CallbackURL=http://localhost:portNumber& AccountId=442311& CustomerId=5521444& DeveloperToken=11112332233&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt") df = pandas.read_sql("SELECT Id, Name FROM AdGroups WHERE CampaignId = '234505536'", engine) df.plot(kind="bar", x="Id", y="Name") plt.show()