title: Feature engineering for timeseries dataset in Python
body: <p>I have a dataset with <code>n</code> observations, where all the observations have <code>m</code> timesteps. I also have a <code>n*m</code> array which contains the label for each timestep on each given observation.</p>
  
  <p>I am doing feature engineering on this dataset to find meaningful features in the data, according to the labels I have. Is there any Python package out there to facilitate this process?</p>
  
  <p>I came across <code>tsfresh</code> (<a href="https://github.com/blue-yonder/tsfresh" rel="nofollow noreferrer">https://github.com/blue-yonder/tsfresh</a>), although it seems like it's only intended to be used when we have a single label to classify each observation, and not a label to classify each timestep, as is my case.</p>