Working with time series can be daunting. My bootcamp instructor showed up to class with a haunted look on the day he prepared to lecture on this topic.
Fortunately, the dtw-python package provides an intuitive way to compare time series. In short, Dynamic Time Warping calculates the distance between two arrays or time series of different length.
First, DTW stretches and/or compresses series of potentially different lengths to make them resemble each other as much as possible. To borrow an example from speech recognition, employing this technique would help an algorithm recognize that “now” and “nowwwwwwww” are the same word, whether spoken by a snappily impatient adult or a tempestuous toddler. After the transform, the package computes the distance between individual aligned elements.
Learn more:
- Download the paper here (originally implemented in R, but still relevant to Python)
- Read up on use cases here