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supy.util.fill_gap_all(ser_to_fill: Series, freq='1D', limit_fill=1, thresh_ratio=0.8) Series[source]#

Fill all gaps in a time series using data from neighbouring divisions of ‘freq’ Parameters#


Time series to gap-fill

freqstr, optional

Frequency to identify gapped divisions, by default ‘1D’

limit_fill: int, optional

Maximum number of consecutive NaNs to fill. Any number less than one means no pre-gap-filling interpolation will be done. Returns#

ser_test_filled: pd.Series

Gap-filled time series. Patterns#

010: missing data in division between others with no missing data 01: missing data in division after one with no missing data 10: division with missing data before one with no missing data