trendypy 0.1.0

A package for trend line clustering.

TrendyPy

TrendyPy is a small Python package for trend line clustering. It is developed to create time series clusters by calculating trend similarity distance with Dynamic Time Warping.

Installation

You can install TrendyPy with pip.

pip install trendypy

TrendyPy depends on Pandas, Numpy and fastdtw and works in Python 3.5+.

Quickstart

Trendy has scikit-learn like api to allow easy integration to existing programs.

>>> from trendypy.trendy import Trendy
>>> a = [1, 2, 3, 4, 5] # increasing trend
>>> b = [1, 2.1, 2.9, 4.4, 5.1] # increasing trend
>>> c = [6.2, 5, 4, 3, 2] # decreasing trend
>>> d = [7, 6, 5, 4, 3, 2, 1] # decreasing trend
>>> trendy = Trendy(n_clusters=2)
>>> trendy.fit([a, b, c, d])
>>> print(trendy.labels_)
[0, 0, 1, 1]
>>> trendy.predict([[0.9, 2, 3.1, 4]]) # another increasing trend
[0]

Refer to this extensive demo to see it in action or just check API Reference for details.

Post

The idea is originated from the post Trend Clustering.