Huffman coding in C++ and analysis using Python

Huffman Coding: An Optimal Data Compression Technique

Huffman coding is a fundamental lossless data compression algorithm that efficiently encodes data by assigning variable-length binary codes based on character frequencies. By creating a binary tree where more frequent characters receive shorter codes, the method minimizes overall data representation length. The algorithm constructs an optimal prefix-free encoding through a systematic process of frequency analysis, node combination, and code generation. Its elegance lies in transforming statistical data characteristics into a compact, efficient representation, making it a cornerstone technique in information theory and digital communication systems for reducing data transmission and storage requirements.

Features:

• Symbol probabilities calculation
• Code word generation
• Encoding/Decoding
• Visualization using python
• Storing results in csv file for further analysis

Dependencies

C++

 gnuplot-iostream

Python

Pandas
Matplotlib
seaborn
numpy

Usage

• Run main.cpp and then use the resultant compression_metrics.csv file for python to run detailed analysis