Manipulating time-series data
We will now examine several common operations that are performed on time-series data. These operations entail realigning data, changing the frequency of the samples and their values, and calculating aggregate results on continuously moving subsets of the data to determine the behavior of the values in the data as time changes. We will examine each of the following:
- Shifting and lagging values to calculate percentage changes
- Changing the frequency of the data in the time series
- Up and down sampling of the intervals and values in the time series
- Performing rolling-window calculations
Shifting and lagging
A common operation on time-series data is to shift the values backward and forward in time. The pandas method for this ...
Get Learning pandas now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.