split timetables into multiple hourly timetables and save as separate .mat files

I have some timeseries sensor data that start at a random time and end at a random time (a sample shown below):

08/05/2019,16:24:37.988776000 	0.464062500000000	4.68968700000000
08/05/2019,16:24:37.989776000 	0.580312500000000	4.75656200000000
08/05/2019,17:24:37.990776000 	0.679687500000000	3.00000000000000
08/05/2019,16:24:37.991776000 	0.472500000000000	4.95500000000000
08/05/2019,18:24:37.992776000 	0.670312500000000	4.75718800000000

I am trying to split the timetable into separate timetables for each hour of data. I've used the discretise function and created a bin column based on the hours each row of data corresponds to using the script:

test = load([dir_file,test_name,'.mat']);
ttab = test.test_timetable; 

binned = discretize(ttab.Var1,'Hour');
tab_binned = table(ttab.Var1,ttab.X,binned);
tab_binned.Properties.VariableNames = {'var2','var1','binned'};
ttab_c_binned = [ttab,tab_binned(:,{'binned'})];

I could use for loops and split the time table and save separate time tables per hour but I wondered if there was a neater way of doing this?

Thanks!

Answer 1

[Peter Perkins]

You can do this in several ways, but honestly the most straight-forward is to write a loop, as shown below. The real question is, why do you want to do this? I'm genuinely asking, because there are tools that let you do things like hourly means without splitting the data up.

Anyways, my solution (which could certainly be tightened up but is at least clear):

>> tt = array2timetable(rand(10,2),'RowTimes',datetime(2019,6,19)+3*hours(sort(rand(10,1))))
tt =
  10×2 timetable
            Time              Var1        Var2  
    ____________________    _________    _______
    19-Jun-2019 00:13:40      0.10665    0.43141
    19-Jun-2019 00:22:11       0.9619    0.91065
    19-Jun-2019 00:33:06    0.0046342    0.18185
    19-Jun-2019 00:43:11      0.77491     0.2638
    19-Jun-2019 00:43:11       0.8173    0.14554
    19-Jun-2019 01:03:10      0.86869    0.13607
    19-Jun-2019 01:12:19     0.084436    0.86929
    19-Jun-2019 01:32:23      0.39978     0.5797
    19-Jun-2019 01:51:58      0.25987    0.54986
    19-Jun-2019 02:33:32      0.80007    0.14495
>> h = unique(tt.Time.Hour)
h =
     0
     1
     2
>> c = cell(length(h),1);
>> for i = 1:length(c), c{i} = tt(tt.Time.Hour == h(i),:); end
>> c{:}
ans =
  5×2 timetable
            Time              Var1        Var2  
    ____________________    _________    _______
    19-Jun-2019 00:13:40      0.10665    0.43141
    19-Jun-2019 00:22:11       0.9619    0.91065
    19-Jun-2019 00:33:06    0.0046342    0.18185
    19-Jun-2019 00:43:11      0.77491     0.2638
    19-Jun-2019 00:43:11       0.8173    0.14554
ans =
  4×2 timetable
            Time              Var1       Var2  
    ____________________    ________    _______
    19-Jun-2019 01:03:10     0.86869    0.13607
    19-Jun-2019 01:12:19    0.084436    0.86929
    19-Jun-2019 01:32:23     0.39978     0.5797
    19-Jun-2019 01:51:58     0.25987    0.54986
ans =
  1×2 timetable
            Time             Var1       Var2  
    ____________________    _______    _______
    19-Jun-2019 02:33:32    0.80007    0.14495