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

Fill all gaps in a time series using data from neighbouring divisions of β€˜freq’

  • ser_to_fill (pd.Series) – Time series to gap-fill

  • freq (str, optional) – Frequency to identify gapped divisions, by default β€˜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.


  • 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)