Overview

The top_charts() function in the pytrends library allows you to retrieve Google’s top charts for a specific year and category. By analyzing this data, you can discover the most popular search queries in various categories, helping you to create engaging and relevant content for your audience.

In this tutorial, we will cover:

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

Retrieve Top Charts 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 top charts data for a specific year and category using the top_charts() function.

# Retrieve top charts data for 2022
top_charts = pytrends.top_charts(date=2022, hl='en-US', tz=360)

This will return a DataFrame containing the top charts data in 2022.

Analyzing the Results

Now, we can analyze the top charts data to identify the most popular search queries in our chosen category.

# Display the top 10 in 2022
print(top_charts.head(10))

This will display the top 10 in 2022, providing valuable insights into the most popular search queries.

Conclusion

In this post, we’ve demonstrated how to use the top_charts() function in the pytrends library to analyze Google’s top charts for data-driven insights. By exploring this data, you can discover the most popular search queries in various categories, helping you to create engaging and relevant content for your audience. This tutorial has covered the process of collecting and analyzing top chart data, from setting up the pytrends request to analyzing the results. Using these insights, you can inform your content strategy and optimize your online presence.

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

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