Pandas: resample a dataframe to match a DatetimeIndex of a different dataframe

Use reindex:

series2.reindex(series1.index)

Output:

2020-06-16 23:16:00     22020-06-16 23:17:00     42020-06-16 23:18:00     62020-06-16 23:19:00     82020-06-16 23:20:00    102020-06-16 23:21:00    122020-06-16 23:22:00    142020-06-16 23:23:00    162020-06-16 23:24:00    182020-06-16 23:25:00    202020-06-16 23:26:00    222020-06-16 23:27:00    242020-06-16 23:28:00    262020-06-16 23:29:00    282020-06-16 23:30:00    302020-06-16 23:31:00    322020-06-16 23:32:00    342020-06-16 23:33:00    362020-06-16 23:34:00    382020-06-16 23:35:00    402020-06-16 23:36:00    422020-06-16 23:37:00    442020-06-16 23:38:00    462020-06-16 23:39:00    482020-06-16 23:40:00    50Freq: T, dtype: int64

Wouldn't a simple resample yield the results are looking for?

series2.resample('T').first()

If your goal is to merge the resampled timestamp back to the first dataset, you could do that as follows:

dt_map = {}for group_label, group_series in series2.resample('T'):    dt_map.update({x:group_label for x in group_series.index})# Overwrite the indexseries2.index = series2.index.map(dt_map)

Note: If you want to perform an aggregate function, stick with the first option.

IIUC, this is what you need:

series2[series2.index.isin(series1.index)]