PyCronos

A comprehensive Python package for data analysis and time series processing.

Features

• Data Loading: Support for multiple file formats (CSV, Excel, JSON, Parquet)
• Data Preprocessing: Missing value handling, normalization, standardization
• Statistical Analysis: Descriptive statistics, hypothesis testing, correlation analysis
• Time Series Analysis: Decomposition, moving averages, outlier detection
• Visualization: Built-in plotting capabilities with matplotlib and seaborn
• Data Validation: Comprehensive data quality checks

Installation

pip install pycronos

For development installation:

git clone https://github.com/yourusername/pycronos.git
cd pycronos
pip install -e ".[dev]"

Quick Start

import pycronos as pc
import pandas as pd

# Load data
loader = pc.DataLoader()
df = loader.auto_load('data.csv')

# Basic preprocessing
preprocessor = pc.Preprocessor()
df_clean = preprocessor.handle_missing_values(df, strategy='fill_mean')

# Descriptive analysis
analysis = pc.DescriptiveAnalysis()
summary = analysis.summary_statistics(df_clean)
correlation = analysis.correlation_matrix(df_clean)

# Visualization
viz = pc.Visualizer()
fig = viz.correlation_heatmap(df_clean)

Package Structure

• core/: Data loading, preprocessing, and validation
• analysis/: Statistical and time series analysis
• visualization/: Plotting and dashboard utilities
• utils/: Helper functions and configuration

Documentation

Full documentation is available at https://pycronos.readthedocs.io/

Contributing

Contributions are welcome! Please read our contributing guidelines and submit pull requests.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Changelog

v0.1.0

• Initial release
• Basic data loading and preprocessing
• Statistical analysis capabilities
• Visualization tools