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

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

Connecting to SerpApi Data

Connecting to SerpApi 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.

Start by setting the Profile connection property to the location of the SerpAPI Profile on disk (e.g. C:\profiles\SerpAPI.apip). Next, set the ProfileSettings connection property to the connection string for SerpAPI (see below).

SerpAPI API Profile Settings

SerpAPI uses API key authentication. To obtain an API key:

1. Sign in to your SerpAPI account at https://serpapi.com
2. Navigate to the API Key page at https://serpapi.com/manage-api-key
3. Copy your private API key

After obtaining your API key, set the following connection properties:

• AuthScheme: Set this to APIKey.

Set the following in the ProfileSettings connection property:

• APIKey: Set this to your SerpAPI private API key.

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

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

engine = create_engine("api:///?Profile=C:\profiles\SerpAPI.apip&AuthScheme=APIKey&ProfileSettings='APIKey=your_api_key_here'")

Execute SQL to SerpApi

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

df = pandas.read_sql("SELECT Asin, Title FROM AmazonSearch WHERE SearchQuery = 'mechanical keyboard'", engine)

Visualize SerpApi Data

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

df.plot(kind="bar", x="Asin", y="Title")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to SerpApi 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("api:///?Profile=C:\profiles\SerpAPI.apip&AuthScheme=APIKey&ProfileSettings='APIKey=your_api_key_here'")
df = pandas.read_sql("SELECT Asin, Title FROM AmazonSearch WHERE SearchQuery = 'mechanical keyboard'", engine)

df.plot(kind="bar", x="Asin", y="Title")
plt.show()