'is there any way to combine overlapping time period from datetime dataframes?
I have 2 dataframes each having two columns indicating the starting and ending of different events in a particular day. the condition is that there will an overlap in the time period across different data frames but no overlap of events will occur in the same data frame.
A new table must be created and if there is any overlap occurring between dataframeA and dataframeB, I need to combine the events such that only the earliest start and last end is present. Also the not overlapping time periods also needs to be present.
e.g.: Dataframe_A
| Startime | End Time |
|---|---|
| 2021-06-20 12:04:48 | 2021-06-20 12:20:37 |
| 2021-06-20 13:04:49 | 2021-06-20 13:08:38 |
| 2021-06-20 13:10:10 | 2021-06-20 13:38:39 |
| 2021-06-20 14:10:34 | 2021-06-20 14:28:40 |
| 2021-06-20 15:06:25 | 2021-06-20 15:24:41 |
Dataframe_B
| Startime | End Time |
|---|---|
| 2021-06-20 12:07:48 | 2021-06-20 12:27:37 |
| 2021-06-20 13:14:49 | 2021-06-20 13:38:38 |
| 2021-06-20 13:40:10 | 2021-06-20 13:58:39 |
| 2021-06-20 14:22:34 | 2021-06-20 14:47:40 |
| 2021-06-20 15:44:25 | 2021-06-20 15:54:41 |
Expected dataframe;
| Column 1 | Column 2 |
|---|---|
| 2021-06-20 12:04:48 | 2021-06-20 12:27:37 |
| 2021-06-20 13:04:49 | 2021-06-20 13:38:38 |
| 2021-06-20 13:40:10 | 2021-06-20 13:58:39 |
| 2021-06-20 14:10:34 | 2021-06-20 14:47:40 |
| 2021-06-20 15:06:25 | 2021-06-20 15:24:41 |
| 2021-06-20 15:44:25 | 2021-06-20 15:54:41 |
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
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