How to join data elements with the same date in a table

Hi everyone, I have a table with the following variables: date, station, value where in each row is represented a value for a station for the specific date.

I would to have a time-series of values for each station:

date1 date 2 date 3

station1 value1 value2 ..... value 100...

.

.

station N value 1 value 2 value 100 ....

That is, I would like to collapse all the elements with the same date together, and then differentiate them based on the station name. In particular I would like to have in each row a time series relative to a particular station.

How could I achieve that?

Thank you.

Answer 1

[Ankriti Sachan]

From the question, it appears that using the Timetables might help you here, though you might get a transpose of the table that you are expecting.

Please refer to this link to know more about creating a timetable using an example.

Answer 2

[Peter Perkins]

This is a one-liner with unstack:

>> date = datetime(2022,1,[1 1 1 2 2 2 3 3 3])';
>> station = categorical(["A" "B" "C" "A" "B" "C" "A" "B" "C"])';
>> value = rand(9,1);
>> tt = timetable(date,station,value)
tt =
  9×2 timetable
       date        station          value       
    ___________    _______    __________________
    01-Jan-2022       A        0.568823660872193
    01-Jan-2022       B        0.469390641058206
    01-Jan-2022       C       0.0119020695012414
    02-Jan-2022       A        0.337122644398882
    02-Jan-2022       B        0.162182308193243
    02-Jan-2022       C        0.794284540683907
    03-Jan-2022       A        0.311215042044805
    03-Jan-2022       B        0.528533135506213
    03-Jan-2022       C        0.165648729499781
>> unstack(tt,"value","station")
ans =
  3×3 timetable
       date                A                    B                    C         
    ___________    _________________    _________________    __________________
    01-Jan-2022    0.568823660872193    0.469390641058206    0.0119020695012414
    02-Jan-2022    0.337122644398882    0.162182308193243     0.794284540683907
    03-Jan-2022    0.311215042044805    0.528533135506213     0.165648729499781