I have a dataframe with time series of categorical values. For a toy example lets say we have o
and v
series. The times may overlap but are not guaranteed to. How can I use a data frame to select the value of each measure at the maximum measurement time?
Here's what the data "looks" like:
9 |
|
| vv
6 | vvvvvvvv vv
| vv vv
measure | vv ooo v
3 | v o oo oo vv
| vvv ooo oo vvv
| vv
0 +------------------------------------
time
Here's a data-frame that represents the data above (obviously incomplete).
series time measure
v 25 1.0
v 26 1.1
o 32 2.2
o 33 2.0
v 28 1.9
...
I'm honestly completely lost here, I've read the docs and they aren't clear on situations like this. Documented aggregation functions seem to act on a series not on a "row".
Using the data graphed above, I should get:
series max_measurement
v 2.0
o 3.0
Edit: this is NOT a duplicate of the linked question. That is simply a multiple aggregate issue. This is an aggregate and selection issue.