Metadata-Version: 1.2
Name: magi
Version: 0.0.8
Summary: high level wrapper for parallel univariate time series forecasting
Home-page: http://github.com/DavisTownsend/forecast
Author: Davis Townsend
Author-email: dtownsend@ea.com
License: MIT
Description: ========
         magi
        ========
        
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        Overview
        ============
        
        `magi` is intended to be a high level python wrapper around other time series forecasting libraries to allow easily parallelized univariate time series forecasting in python. In particular, the library current supports wrappers around the 
        R `forecast <https://www.rdocumentation.org/packages/forecast/versions/8.3>`_ library and 
        facebook's `prophet <https://github.com/facebook/prophet>`_ package
        
        
        Basic Usage
        ============
        
        Use Cases
        ============
        
        What this package should be used for
        ------------
        * forecasting for 1 or more Univariate Time Series
        * forecasting using many different time series models in parallel with minimal effort
        * wrapper for R forecast library to implement those models in python workflow
        * wrapper around Prophet library to provide easier data framework to work with
        * single source of access for many different time series forecasting models 
        
        What this package should NOT be used for
        ------------
        * Multivariate Time Series data. If you have multiple x variables that are correlated with your response variable, I'd suggest simply using regression with lags and seasonal variable to account for autocorrelation in your error
        * Data exploration - The time series analysis step is much more suited to using the R forecast package directly
        
        Dependencies
        ============
        * dask
        * distributed
        * plotly
        * cufflinks
        * rpy2 (& forecast package >=8.3 installed in R)
        * fbprophet
        
        
        Installation
        ============
        
        .. code-block:: console
        
           $ pip install magi
        
        
        Documentation
        ============
        
        Documentation is hosted on `Read the Docs <http://magi-docs.readthedocs.io/en/latest/index.html>`_.
        
        Disclaimer
        ============
        This package is still very early in development and should not be relied upon in production. Everything is still subject to change
        
Keywords: time series analysis forecast forecasting predict model parallel
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Requires-Python: ~=3.5
