Cskvdhdgzip

No data is lost; decompressing restores the exact original file.

Gzip ( .gz ) is a widely used, open-source algorithm and file format developed in 1992 by Jean-loup Gailly and Mark Adler to replace proprietary compression tools. It is the standard for web compression and is frequently used to shrink large, text-heavy files, such as CSVs, to save storage space and increase transfer speeds.

import gzip import shutil # Compress with open('data.csv', 'rb') as f_in: with gzip.open('data.csv.gz', 'wb') as f_out: shutil.copyfileobj(f_in, f_out) # Decompress with gzip.open('data.csv.gz', 'rb') as f_in: with open('data_restored.csv', 'wb') as f_out: shutil.copyfileobj(f_in, f_out) Use code with caution. Copied to clipboard Working with Pandas cskvdhdgzip

import pandas as pd # Write DataFrame to Gzip CSV df.to_csv("data.csv.gz", index=False, compression="gzip") # Read Gzip CSV df = pd.read_csv("data.csv.gz", compression="gzip") Use code with caution. Copied to clipboard Gzip vs. Other Formats How Gzip Compression Works

Gzip operates using a combination of two primary algorithms, often referred to as : No data is lost; decompressing restores the exact

This combination results in a file with a .gz extension, which is often significantly smaller than the original, especially for CSVs, logs, or JSON files. Advantages and Limitations

Excellent at compressing text files (frequently over 80% compression ratios for large CSVs). import gzip import shutil # Compress with open('data

Pandas can directly read and write compressed files, making it convenient for large datasets.