TimeSeriesDataFrame.to_regular_index

TimeSeriesDataFrame.to_regular_index(freq: str) → TimeSeriesDataFrame

Fill the gaps in an irregularly-sampled time series with NaNs.

Parameters

freq (str) – Frequency string of the new time series data index.

Examples

>>> print(ts_dataframe)
                    target
item_id timestamp
0       2019-01-01     NaN
        2019-01-03     1.0
        2019-01-06     2.0
        2019-01-07     NaN
1       2019-02-04     3.0
        2019-02-07     4.0

>>> print(ts_dataframe.to_regular_index(freq="D"))
                    target
item_id timestamp
0       2019-01-01     NaN
        2019-01-02     NaN
        2019-01-03     1.0
        2019-01-04     NaN
        2019-01-05     NaN
        2019-01-06     2.0
        2019-01-07     NaN
1       2019-02-04     3.0
        2019-02-05     NaN
        2019-02-06     NaN
        2019-02-07     4.0