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Python Connector Libraries for Bing Search Data Connectivity. Integrate Bing Search with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

How to Visualize Bing Search Data in Python with pandas

Use pandas and other modules to analyze and visualize live Bing Search results 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 Search, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Bing Search-connected Python applications and scripts for visualizing Bing Search results. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Bing Search results, execute queries, and visualize the results.

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

Connecting to Bing Search Results

Connecting to Bing Search results 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 Bing, set the ApiKey connection property. To obtain the API key, sign into Microsoft Cognitive Services and register for the Bing Search APIs.

Two API keys are then generated; select either one.

When querying tables, the SearchTerms parameter must be supplied in the WHERE clause.

Follow the procedure below to install the required modules and start accessing Bing Search 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 Search Results in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Bing Search results.

engine = create_engine("bing:///?APIKey=MyAPIKey")

Execute SQL to Bing Search

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

df = pandas.read_sql("SELECT Title, ViewCount FROM VideoSearch WHERE SearchTerms = 'WayneTech'", engine)

Visualize Bing Search Results

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

df.plot(kind="bar", x="Title", y="ViewCount")

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Bing Search to start building Python apps and scripts with connectivity to Bing Search results. 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("bing:///?APIKey=MyAPIKey")
df = pandas.read_sql("SELECT Title, ViewCount FROM VideoSearch WHERE SearchTerms = 'WayneTech'", engine)

df.plot(kind="bar", x="Title", y="ViewCount")