Posts Tagged‘TimeSeries’

TimeSeries Decomposition in Python with statsmodels and Pandas

by Paul Balzer on 3. Januar 2016

5 Comments

A lot of data is recorded in time domain, which means you will have a datapoint in the form of

timestamp: value

A useful approach to get insights into the data is, to decompose the timeseries. That usually means, you seperate your data into

  • seasonal
  • trend
  • residual

This famous library from R (`decompose`) is available in Python via statsmodel since version 0.6. Yeah! Let’s take a look into it with the parking lot data of city of Dresden.

Continue Reading