statflow 3.4.6

A versatile statistical toolkit for Python, featuring core statistical methods, time series analysis, signal processing, and climatology tools

StatFlow

A Python library for statistical analysis and data flow management.

Features

• Statistical Analysis

  • Descriptive statistics
  • Hypothesis testing
  • Regression analysis
  • Time series analysis
  • Probability distributions

• Data Flow Management

  • Data pipeline construction
  • ETL operations
  • Data validation
  • Data transformation
  • Data quality checks

• Visualisation

  • Statistical plots
  • Distribution visualisations
  • Time series plots
  • Correlation matrices
  • Custom charting

• Data Processing

  • Data cleaning
  • Feature engineering
  • Data normalisation
  • Outlier detection
  • Missing value handling

Installation

Prerequisites

• Python 3.8 or higher
• pip or conda package manager

Using pip

pip install statflow

Using conda

conda install -c conda-forge statflow

Usage

Basic Usage

from statflow import DataFlow, StatisticalAnalysis

# Create a data flow pipeline
flow = DataFlow()
flow.load_data("data.csv")
flow.clean_data()
flow.transform_data()

# Perform statistical analysis
analysis = StatisticalAnalysis(flow.data)
summary = analysis.descriptive_stats()
correlation = analysis.correlation_matrix()

Advanced Usage

from statflow import TimeSeries, HypothesisTest

# Time series analysis
ts = TimeSeries("time_series_data.csv")
trend = ts.decompose()
forecast = ts.predict(steps=10)

# Hypothesis testing
test = HypothesisTest(sample1, sample2)
result = test.t_test()
p_value = result.p_value

Project Structure

statflow/
├── statflow/              # Main package directory
│   ├── core/             # Core functionality
│   │   ├── flow.py      # Data flow management
│   │   └── stats.py     # Statistical analysis
│   ├── analysis/         # Analysis modules
│   │   ├── descriptive.py # Descriptive statistics
│   │   └── inferential.py # Inferential statistics
│   └── utils/            # Utility functions
│       ├── visualization.py # Plotting utilities
│       └── preprocessing.py # Data preprocessing
├── tests/                # Test suite
├── docs/                 # Documentation
└── examples/             # Usage examples

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Development Setup

1. Clone the repository:

   git clone https://github.com/yourusername/statflow.git
   cd statflow
   

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install development dependencies:

   pip install -e ".[dev]"
   

Testing

Run the test suite:

pytest

License

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

Acknowledgments

• Thanks to all contributors who have helped improve this library
• Inspired by various statistical analysis tools and data flow frameworks

Contact

For questions or suggestions, please open an issue on GitHub or contact the maintainers.