Overview

The interest_over_time() function in the pytrends library allows you to retrieve the interest in specific keywords over time. By analyzing this data, you can gain insights into how the interest in a keyword has evolved, helping you to make informed decisions about your content strategy and marketing efforts.

In this tutorial, we will cover:

  1. Defining the list of keywords
  2. Setting the time range
  3. Retrieving interest over time data
  4. Analyzing the results

Define the List of Keywords

First, we need to define the list of keywords for which we want to analyze the interest over time.

keywords = ['Python', 'JavaScript']

Set the Time Range

Next, we need to set the time range for which we want to analyze the interest in our keywords. In this example, we will analyze the interest over the past year.

time_range = '2022-01-01 2023-01-31'

Retrieve Interest Over Time Data

Now, we need to retrieve the interest over time data for our keywords and time range using the interest_over_time() function.

from pytrends.request import TrendReq

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

# Build the payload
pytrends.build_payload(keywords, cat=0, timeframe=time_range, geo='', gprop='')

# Retrieve interest over time data
interest_over_time_data = pytrends.interest_over_time()

This will return a DataFrame containing the interest over time data for our keywords.

Analyzing the Results

Now, we can analyze the interest over time data to understand the performance and popularity of our keywords.

print(interest_over_time_data.head())

This will display the interest over time data, providing valuable insights into the performance and popularity of our keywords.

Conclusion

In this post, we’ve demonstrated how to use the interest_over_time() function in the pytrends library to analyze the interest in specific keywords over time. By analyzing this data, you can gain insights into how the interest in a keyword has evolved, helping you make informed decisions about your content strategy, marketing efforts, and even product development. By harnessing interest over time analysis, you can stay ahead of the competition and ensure that your content and products remain relevant and appealing to your target audience.

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

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