f2a 0.1.0

File to Analysis — Automatically perform descriptive statistical analysis and visualization from any data source

f2a — File to Analysis

A Python library that automatically performs descriptive statistical analysis and visualization from data sources

Installation

pip install f2a

# With HuggingFace dataset support
pip install f2a[hf]

# All features
pip install f2a[all]

Quick Start

import f2a

# Analyze a local CSV file
report = f2a.analyze("data/sales.csv")
report.show()  # Print summary to console

# Analyze a Hugging Face dataset
report = f2a.analyze("hf://imdb")
report.show()

# Access detailed results
report.stats.summary        # Summary statistics DataFrame
report.stats.correlation     # Correlation matrix
report.viz.plot_distributions()  # Distribution plots

Supported Formats

Format	Extensions	Extra Install
CSV / TSV	.csv, .tsv	—
JSON / JSONL	.json, .jsonl	—
Parquet	.parquet	pip install f2a[parquet]
Excel	.xlsx, .xls	pip install f2a[excel]
SQLite	.db, .sqlite3	—
Stata	.dta	—
XML / HTML	.xml, .html	—
HuggingFace	hf://dataset_name	pip install f2a[hf]

Analysis Features

• Descriptive Statistics: Mean, median, standard deviation, quantiles, mode, etc.
• Distribution Analysis: Skewness, kurtosis, normality tests
• Correlation Analysis: Pearson, Spearman, Cramér's V
• Missing Data Analysis: Missing ratio, pattern analysis
• Visualization: Histograms, boxplots, correlation heatmaps, missing data matrix

Development

git clone https://github.com/CocoRoF/f2a.git
cd f2a
pip install -e ".[dev]"
pytest

License

MIT License — See LICENSE for details.