Python-Based Google Trends Analyzation

Google Search Trends Analysis (Python)

## Project Overview

This project analyzes **Google Search Trends data** using Python to understand how a keyword's popularity changes over time and across regions. The analysis covers **15 countries**, compares **time-wise interest**, and explores **related keywords** to uncover search behavior patterns.

## Objectives

* Analyze time-wise search interest of a keyword
* Compare keyword popularity across 15 countries
* Identify and analyze related search keywords
* Visualize trends for better insights

## Tools & Technologies

* Python
* Pytrends (Google Trends API Wrapper)
* Pandas
* NumPy
* Matplotlib
* Seaborn
* Jupyter Notebook

## Project Structure

```
├── google data analysis project.ipynb # Main notebook
├── README.md # Project documentation
```

## Key Analysis

* Interest over time (trend analysis)
* Country-wise keyword comparison
* Related queries and keywords analysis
* Data visualization using line charts and bar plots

## How to Run

1. Clone the repository
2. Install required libraries:

```bash
pip install pytrends pandas matplotlib seaborn
```
3. Open the Jupyter Notebook
4. Run the cells step by step

## Results & Insights

The project reveals how search interest varies by country and time, highlights peak search periods, and shows how related keywords trend alongside the main keyword.

## Future Improvements

* Analyze multiple keywords together
* Add real-time trend monitoring
* Apply forecasting models

## Author

Amit

## License

This project is for educational purposes only.