python - downsampling data using timestamp information -
i have array of arbitrary data x
, associated timestamps t
correspond data in x
(they same length n
).
i want downsample data x
smaller length m < n
, such new data equally spaced in time (by using timestamp information). instead of decimating data taking every nth datapoint. using closest time-neighbor fine.
scipy has resampling code, tries interpolate between data points, cannot data. numpy or scipy have code this?
for example, suppose want downsample letters of alphabet according logarithmic time:
import string import numpy np x = string.lowercase[::] t = np.logspace(1, 10, num=26) y = downsample(x, t, 8)
i'd suggest using pandas
, resample
function:
convenience method frequency conversion , resampling of regular time-series data.
note how
parameter in particular.
you can convert numpy array dataframe:
import pandas pd yourpandasdf = pd.dataframe(yournumpyarray)
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