Check out the new video on timeseries, completing the tutorials of how to segment data for more effective aggregation. In the first two videos I showed how to do this in excel and libre office, the next video uses more technical methods.

This video uses the pandas library with some help from datetime to slice up our data following the previous example. Pandas will be a common tool for data munging and is very versatile. The methods shown in this video are aimed at providing a range of techniques in which to manipulate time, including standard column formatting, lambda statements, and list comprehension.

If you like this video or have requests for other comment leave a comment! Stay tuned for the next video which I will show basic techniques for graphing in python.

Link to file used in the video:

https://github.com/BrianS3/Python/blob/master/pandas/timeseries/pandas_basics_timeseries.ipynb