Zipf's Law in Lady Gaga's Lyrics

This project analyzes Lady Gaga's song lyrics to examine the application of Zipf's Law in her music. Zipf's Law is a linguistic principle stating that the frequency of a word is inversely proportional to its rank in the frequency table.

Project Overview

This data analysis project:

• Processes and cleans Lady Gaga's song lyrics
• Analyzes word frequency distribution
• Tests whether the lyrics follow Zipf's Law
• Visualizes the results through various charts and plots

Dataset

The project uses a dataset (LadyGaga.csv) containing Lady Gaga's song lyrics. The dataset includes:

• Song titles
• Album information
• Complete lyrics for each song

Installation and Setup

Prerequisites

• Python 3.6+
• Jupyter Notebook

Required Libraries

pip install pandas numpy matplotlib seaborn

Usage

1. Clone this repository
2. Open the Jupyter Notebook:

   jupyter notebook Hackdev.ipynb

3. Run the cells to reproduce the analysis

Analysis and Results

The analysis includes:

1. Data Cleaning and Preprocessing:

   • Removing missing values
   • Tokenizing lyrics
   • Converting text to lowercase

2. Word Frequency Analysis:

   • Counting word occurrences
   • Ranking words by frequency

3. Zipf's Law Verification:

   • Comparing actual word frequencies with expected frequencies according to Zipf's Law
   • Log-log plotting of rank vs. frequency

4. Visualization:

   • Bar charts of top words
   • Log-log plots showing the relationship between word rank and frequency

Key Findings

The analysis demonstrates how closely Lady Gaga's lyrics follow Zipf's Law, providing insights into linguistic patterns in popular music.

Files in the Repository

• Hackdev.ipynb: Jupyter notebook containing the complete analysis
• LadyGaga.csv: Dataset with Lady Gaga's song lyrics
• zipf_analysis.png: Log-log plot of word rank vs. frequency
• top_words.png: Visualization of the most frequent words
• top_words_chart.png: Bar chart of the top words

License

This project is available for educational purposes.

Contact

For questions or feedback about this analysis, please open an issue in this repository.