I would like to be able to find out what time it takes for the values in one column to change, based on when the value changes in another column. I have loaded an example of the table below.
| 23-02-03 12:01:27.213000 | 60 | 0 |
| 23-02-03 12:01:27.243000 | 60 | 0 |
| 23-02-03 12:01:27.313000 | 60 | 0 |
| 23-02-03 12:01:27.353000 | 50 | 0 |
| 23-02-03 12:01:27.413000 | 50 | 0 |
| 23-02-03 12:01:27.453000 | 50 | 0 |
| 23-02-03 12:01:27.513000 | 50 | 10 |
| 23-02-03 12:01:27.553000 | 50 | 10 |
| 23-02-03 12:01:27.613000 | 50 | 10 |
| 23-02-03 12:01:27.653000 | 50 | 10 |
| 23-02-03 12:01:27.713000 | 50 | 10 |
| 23-02-03 12:01:27.753000 | 50 | 10 |
| 23-02-03 12:01:27.813000 | 50 | 10 |
| 23-02-03 12:01:27.853000 | 49.5 | 10 |
| 23-02-03 12:01:27.913000 | 49.5 | 10 |
| 23-02-03 12:01:27.953000 | 49.5 | 10 |
| 23-02-03 12:01:28.013000 | 49.5 | 10 |
| 23-02-03 12:01:28.053000 | 49.5 | 10 |
| 23-02-03 12:01:28.113000 | 49.5 | 10 |
| 23-02-03 12:01:28.153000 | 49.5 | 10 |
| 23-02-03 12:01:28.213000 | 49.5 | 10 |
| 23-02-03 12:01:28.253000 | 49.5 | 25 |
| 23-02-03 12:01:28.313000 | 49.5 | 25 |
| 23-02-03 12:01:28.353000 | 49.5 | 25 |
| 23-02-03 12:01:28.423000 | 49.5 | 25 |
| 23-02-03 12:01:28.453000 | 48.3 | 25 |
| 23-02-03 12:01:28.533000 | 48.3 | 25 |
| 23-02-03 12:01:28.553000 | 48.3 | 25 |
| 23-02-03 12:01:28.634000 | 48.3 | 25 |
| 23-02-03 12:01:28.653000 | 48.3 | 25 |
| 23-02-03 12:01:28.743000 | 48.3 | 33 |
| 23-02-03 12:01:28.753000 | 48.3 | 33 |
| 23-02-03 12:01:28.843000 | 48.3 | 33 |
| 23-02-03 12:01:28.853000 | 48.3 | 33 |
| 23-02-03 12:01:28.943000 | 48.3 | 33 |
| 23-02-03 12:01:28.953000 | 48.3 | 33 |
| 23-02-03 12:01:29.043000 | 48.3 | 33 |
| 23-02-03 12:01:29.053000 | 48.3 | 33 |
| 23-02-03 12:01:29.143000 | 48.3 | 33 |
| 23-02-03 12:01:29.153000 | 48.3 | 33 |
| 23-02-03 12:01:29.243000 | 48.3 | 33 |
| 23-02-03 12:01:29.253000 | 48.3 | 33 |
| 23-02-03 12:01:29.343000 | 48.3 | 33 |
| 23-02-03 12:01:29.353000 | 49.1 | 33 |
| 23-02-03 12:01:29.443000 | 49.1 | 33 |
| 23-02-03 12:01:29.463000 | 49.1 | 33 |
| 23-02-03 12:01:29.543000 | 49.1 | 59 |
| 23-02-03 12:01:29.563000 | 49.1 | 59 |
So the first column is time stamp. When the value on column 1 changes from 50 to 49.5, the value in the third column changes a while after.
From this example col A changes from 60 to 50 at 27.353 col b changes from 0 to 10 at 27.513
So it takes .160 secs for the value in col b to change after the value changes in col a.
I would like to be able to use a python script to calculate this time difference, and also the average time difference.
I have just taken out the values to show below
| First Change | | |
|--------------------------|------|----|
| 23-02-03 12:01:27.353000 | 50 | |
| 23-02-03 12:01:27.513000 | | 10 |
| Time diff | | |
| 0.16 | | |
| Second change | | |
| 23-02-03 12:01:27.853000 | 49.5 | |
| 23-02-03 12:01:28.253000 | | 25 |
| Time diff | | |
| 0.4 | | |
| Third change | | |
| 23-02-03 12:01:28.453000 | 48.3 | |
| 23-02-03 12:01:28.743000 | | 33 |
| Time diff | | |
| 0.29 | | |
| Fourth change | | |
| 23-02-03 12:01:29.353000 | 49.1 | |
| 23-02-03 12:01:29.543000 | | 59 |
| 0.19 | | |
| Average Time diff | | |
| 0.26 | | |
thanks
So, I have been able to get the differences by the following code
df['Change 1'] = df['Col1'].diff()
df['Change 2'] = df['Col2'].diff()
This stores when col1 changes and when col2 changes, as seen below. But I am not sure how to get the time diff when between them
| Datetime | Col1 | Col2 | Change 1 | Change 2 |
|----------------------------|------|------|----------|----------|
| 23-02-03 12:01:27.213000 | 60 | 0 | 0 | 0 |
| 23-02-03 12:01:27.243000 | 60 | 0 | 0 | 0 |
| 23-02-03 12:01:27.313000 | 60 | 0 | 0 | 0 |
| 23-02-03 12:01:27.353000 | 50 | 0 | 10 | 0 |
| 23-02-03 12:01:27.413000 | 50 | 0 | 0 | 0 |
| 23-02-03 12:01:27.453000 | 50 | 0 | 0 | 0 |
| 23-02-03 12:01:27.513000 | 50 | 10 | 0 | 10 |
| 23-02-03 12:01:27.553000 | 50 | 10 | 0 | 0 |
| 23-02-03 12:01:27.613000 | 50 | 10 | 0 | 0 |
| 23-02-03 12:01:27.653000 | 50 | 10 | 0 | 0 |
| 23-02-03 12:01:27.713000 | 50 | 10 | 0 | 0 |
| 23-02-03 12:01:27.753000 | 50 | 10 | 0 | 0 |
| 23-02-03 12:01:27.813000 | 50 | 10 | 0 | 0 |
| 23-02-03 12:01:27.853000 | 49.5 | 10 | 0.5 | 0 |
| 23-02-03 12:01:27.913000 | 49.5 | 10 | 0 | 0 |
| 23-02-03 12:01:27.953000 | 49.5 | 10 | 0 | 0 |
| 23-02-03 12:01:28.013000 | 49.5 | 10 | 0 | 0 |
| 23-02-03 12:01:28.053000 | 49.5 | 10 | 0 | 0 |
| 23-02-03 12:01:28.113000 | 49.5 | 10 | 0 | 0 |
| 23-02-03 12:01:28.153000 | 49.5 | 10 | 0 | 0 |
| 23-02-03 12:01:28.213000 | 49.5 | 10 | 0 | 0 |
| 23-02-03 12:01:28.253000 | 49.5 | 25 | 0 | 15 |
| 23-02-03 12:01:28.313000 | 49.5 | 25 | 0 | 0 |
| 23-02-03 12:01:28.353000 | 49.5 | 25 | 0 | 0 |
| 23-02-03 12:01:28.423000 | 49.5 | 25 | 0 | 0 |
| 23-02-03 12:01:28.453000 | 48.3 | 25 | 1.2 | 0 |
| 23-02-03 12:01:28.533000 | 48.3 | 25 | 0 | 0 |
| 23-02-03 12:01:28.553000 | 48.3 | 25 | 0 | 0 |
| 23-02-03 12:01:28.634000 | 48.3 | 25 | 0 | 0 |
| 23-02-03 12:01:28.653000 | 48.3 | 25 | 0 | 0 |
| 23-02-03 12:01:28.743000 | 48.3 | 33 | 0 | 8 |
| 23-02-03 12:01:28.753000 | 48.3 | 33 | 0 | 0 |
| 23-02-03 12:01:28.843000 | 48.3 | 33 | 0 | 0 |
| 23-02-03 12:01:28.853000 | 48.3 | 33 | 0 | 0 |
| 23-02-03 12:01:28.943000 | 48.3 | 33 | 0 | 0 |
| 23-02-03 12:01:28.953000 | 48.3 | 33 | 0 | 0 |
| 23-02-03 12:01:29.043000 | 48.3 | 33 | 0 | 0 |
| 23-02-03 12:01:29.053000 | 48.3 | 33 | 0 | 0 |
| 23-02-03 12:01:29.143000 | 48.3 | 33 | 0 | 0 |
| 23-02-03 12:01:29.153000 | 48.3 | 33 | 0 | 0 |
| 23-02-03 12:01:29.243000 | 48.3 | 33 | 0 | 0 |
| 23-02-03 12:01:29.253000 | 48.3 | 33 | 0 | 0 |
| 23-02-03 12:01:29.343000 | 48.3 | 33 | 0 | 0 |
| 23-02-03 12:01:29.353000 | 49.1 | 33 | 0.8 | 0 |
| 23-02-03 12:01:29.443000 | 49.1 | 33 | 0 | 0 |
| 23-02-03 12:01:29.463000 | 49.1 | 33 | 0 | 0 |
| 23-02-03 12:01:29.543000 | 49.1 | 59 | 0 | 26 |
| 23-02-03 12:01:29.563000 | 49.1 | 59 | 0 | 0 |
I've had an idea, if I was able to drop the values in-between then this might make it easier to check
