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.