Overview

The trending_searches() function in the pytrends library allows you to retrieve the current trending searches on Google. By analyzing this data, you can gain insights into the latest trends and topics that are capturing the attention of your audience, helping you to create timely and relevant content.

In this tutorial, we will cover:

  1. Importing the necessary libraries
  2. Setting up the pytrends request
  3. Retrieving trending searches data
  4. Analyzing the results

Retrieve Trending Searches Data

First, we need to import the necessary libraries and set up our pytrends request.

from pytrends.request import TrendReq

# Set up pytrends request
pytrends = TrendReq(hl='en-US', tz=360)

Next, we’ll retrieve the current trending searches on Google using the trending_searches() function.

# Retrieve trending searches data
trending_searches = pytrends.trending_searches(pn='united_states')

This will return a DataFrame containing the current trending searches in the United States.

Analyzing the Results

Now, we can analyze the trending searches data to identify new opportunities for content creation and optimization.

# Display the top 10 trending searches
print(trending_searches.head(10))

This will display the top 10 trending searches, providing valuable insights into the latest trends and topics that are capturing the attention of your audience.

Conclusion

In this post, we’ve demonstrated how to use the trending_searches() function in the pytrends library to track trending searches on Google. By analyzing this data, you can stay ahead of the curve and discover new opportunities for content creation and optimization. This tutorial has covered the process of collecting and analyzing trending search data, from setting up the pytrends request to analyzing the results. Using these insights, you can create timely and relevant content for your audience.

NOTE : pytrends uses an unofficial API. Please use here for issues.

SAMPLE CODE : https://github.com/hobbyworker/google-trend-for-python