Resampling time series

Resampling describes the process of frequency conversion over time series data. It is a helpful technique in various circumstances as it fosters understanding by grouping together and aggregating data. It is possible to create a new time series from daily temperature data that shows the average temperature per week or month. On the other hand, real-world data may not be taken in uniform intervals and it is required to map observations into uniform intervals or to fill in missing values for certain points in time. These are two of the main use directions of resampling: binning and aggregation, and filling in missing data. Downsampling and upsampling occur in other fields as well, such as digital signal processing. There, the process of downsampling is often called decimation and performs a reduction of the sample rate. The inverse process is called interpolation, where the sample rate is increased. We will look at both directions from a data analysis angle.