Metadata-Version: 2.1
Name: FillingTimeSeries
Version: 0.8.1
Summary: Filling Time series: Package to fill missing values in geophysical time series in Python
Home-page: https://github.com/rolandojduartem/FillingTimeSeries
Author: Rolando Jesus Duarte Mejias, Erick Rivera Fernandez
Author-email: rolando.duartemejias@ucr.ac.cr
License: MIT
Download-URL: https://github.com/rolandojduartem/FillingTimeSeries/archive/refs/tags/v_0_8_1.tar.gz
Keywords: Time Series,Missing values,Metereology,Geophysics,Metereological
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: LICENSE.txt

# Filling Time Series

## Filling missing values in geophysical time series

![FTS|FillingTimeSeries](https://repository-images.githubusercontent.com/404879203/f4deb7ec-6b24-4ca9-89eb-f1efc8d2fd55)

![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge&logo=python&logoColor=ffdd54) [![PyPI pyversions](https://img.shields.io/pypi/pyversions/FillingTimeSeries.svg)](https://pypi.python.org/pypi/FillingTimeSeries/) [![PyPI status](https://img.shields.io/pypi/status/FillingTimeSeries.svg)](https://pypi.python.org/pypi/FillingTimeSeries/) [![PyPI license](https://img.shields.io/pypi/l/FillingTimeSeries.svg)](https://pypi.python.org/pypi/FillingTimeSeries/)

## About Filling Time Series
Filling Time Series is a Python package to help professionals work with geophysical time series by filling missing values in their data developed at the Centro de Investigaciones GeofÃ­sicas (CIGEFI), Universidad de Costa Rica (UCR).

## Last updates
- Fixing Ulrych and Clayton Method (Alfaro & Soley, 2009)(UreÃ±a, Alfaro & Soley, 2016)

## Documentation
Documentation will be available soon.

## Features

- Autoregression-based method
- Principal-components-based method

## Dependencies

- [Scikit-learn](https://scikit-learn.org) For principal-components-based method
- [Statsmodels](https://www.statsmodels.org/) For autoregression-based method
- [Matplotlib](https://matplotlib.org/) Plotting data
- [Pandas](https://pandas.pydata.org/) Data handler
- [Numpy](https://numpy.org/) Mathematical operations in arrays

## Installation

- Using pip:

```
pip install FillingTimeSeries
```

## Bug report
Bug reports can be submitted to the issue tracker at:

[https://github.com/rolandojduartem/FillingTimeSeries/issues](https://github.com/rolandojduartem/FillingTimeSeries/issues)

## License

MIT License

**Free Software**

