Change Frequency

Resample a dataset to a different time frequency, interpolating up or aggregating down.

Every dataset has a frequency — daily, weekly, monthly, quarterly or yearly. The Change Frequency step converts between them and recalculates the values accordingly.

Moving from a higher to a lower frequency requires an aggregation formula, such as average or end of period. Moving from a lower to a higher frequency requires an interpolation formula, such as linear interpolation or splines.

How to resample

1. Create a pipeline and choose the data source
2. Add a Change Sample Frequency step

   The system detects the input frequency automatically.

   
3. Select the output frequency

   This determines whether the step interpolates or downscales.

   Going up in frequency (monthly to daily) offers 9 interpolation options: Repeat, Linear, Quadratic, Cubic, Polynomial order 3, Piecewise Polynomial, Spline, Krogh, and Fill with 0.

   Going down in frequency (monthly to quarterly) offers 6 aggregations: Average, Sum, Min, Max, Last and First.

   

Interpolating to a higher frequency invents data points that were never observed. It is appropriate for aligning series before a join, but the interpolated values should not be treated as measurements.

Next steps

Merge branches

Join series once they share a frequency.

Apply transform

Frequency-aware transformations like year-over-year change.