Overview

The realtime_trending_searches() function in the pytrends library allows you to retrieve real-time 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, relevant, and engaging content.

In this tutorial, we will cover:

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

Retrieve Real-Time 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 real-time trending searches on Google using the realtime_trending_searches() function.

# Retrieve real-time trending searches data
realtime_trending_searches = pytrends.realtime_trending_searches(pn='US')

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

Analyzing the Results

Now, we can analyze the real-time trending searches data to identify the latest trends and topics that are capturing the attention of our audience.

# Display the top 10 real-time trending searches
print(realtime_trending_searches.head(10))

This will display the top 10 real-time 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 realtime_trending_searches() function in the pytrends library to discover real-time trending searches on Google. By analyzing this data, you can stay on top of the latest trends and topics, helping you create timely, relevant, and engaging content. This tutorial has covered the process of collecting and analyzing real-time trending search data, from setting up the pytrends request to analyzing the results. Using these insights, you can create content that resonates with your audience and capitalizes on current trends.

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

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