# Separate time series data in Individual Months

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Ben Whitby le 18 Mar 2023
Commenté : Star Strider le 20 Mar 2023
Hi ALL,
I have a large time series of data sampled every 5 minutes starting '01-Oct-2021 00:00:00' and ending '28-Feb-2023 23:54:59'. There are two columns one is datetime(dd:MM:yyyy:HH:mm:ss) and the other is a variable called Volts A-N. It goes as follows
Time Volts A-N
'01-Oct-2021 04:59:59' 120
'01-Oct-2021 05:04:59' 130
'01-Oct-2021 05:09:59' 123
'01-Oct-2021 05:14:59' 145
'01-Oct-2021 05:19:59' 123
'01-Oct-2021 05:24:59' 133
'01-Oct-2021 05:29:59' 132
'01-Oct-2021 05:34:59' 134
'01-Oct-2021 05:39:59' 134
'01-Oct-2021 05:44:59' 132
'01-Oct-2021 05:49:59' 123
etc until
'28-Feb-2023 23:54:59' 157
Is there an easy way to split the data into individual months by finding the index of the data value corresponding to the start and end of each month? I want to be able to calculate the mean and standard deviation of the data in each individual month. Obviously if the months were all the same lengths I could simply use reshape() function but they are not. Any help would be appreciated.
Thanks
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Ben Whitby le 20 Mar 2023
Thank you, This works.
Star Strider le 20 Mar 2023
As always, my pleasure!

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### Réponse acceptée

Star Strider le 18 Mar 2023
It’s not necessary to determine the beginning and dne of each month to separate them.
This approach uses the ymd function with findgroups to separate the dates by month and year, and then uses accumarray to do the ‘heavy lifting’ to separate the resulting table by month and year.
Try something like this —
Start = datetime('01-Oct-2021 00:00:00');
End = datetime('28-Feb-2023 23:54:59');
DTV = (Start : minutes(5) : End).'; % Date Time Vector
DateVolts = table(DTV, randi([120 160],size(DTV)), 'VariableNames',{'Time','Volts A-H'}) % Create Data Table
DateVolts = 148607×2 table
Time Volts A-H ____________________ _________ 01-Oct-2021 00:00:00 142 01-Oct-2021 00:05:00 160 01-Oct-2021 00:10:00 140 01-Oct-2021 00:15:00 152 01-Oct-2021 00:20:00 139 01-Oct-2021 00:25:00 155 01-Oct-2021 00:30:00 155 01-Oct-2021 00:35:00 122 01-Oct-2021 00:40:00 158 01-Oct-2021 00:45:00 120 01-Oct-2021 00:50:00 143 01-Oct-2021 00:55:00 120 01-Oct-2021 01:00:00 150 01-Oct-2021 01:05:00 148 01-Oct-2021 01:10:00 127 01-Oct-2021 01:15:00 132
[y,m,d] = ymd(DateVolts.Time); % Return Year, Month, & Day
[G,IDm,IDy] = findgroups(y,m); % Create Group Reference
MonthsByYear = accumarray(G,(1:size(DateVolts,1)).', [], @(x){DateVolts(x,:)}) % Segment By Month & Year
MonthsByYear = 17×1 cell array
{8928×2 table} {8640×2 table} {8928×2 table} {8928×2 table} {8064×2 table} {8928×2 table} {8640×2 table} {8928×2 table} {8640×2 table} {8928×2 table} {8928×2 table} {8640×2 table} {8928×2 table} {8640×2 table} {8928×2 table} {8928×2 table}
MonthsByYear{1}([1 end],:) % First Month In Series
ans = 2×2 table
Time Volts A-H ____________________ _________ 01-Oct-2021 00:00:00 142 31-Oct-2021 23:55:00 156
MonthsByYear{17}([1 end],:) % Last Month In Series
ans = 2×2 table
Time Volts A-H ____________________ _________ 01-Feb-2023 00:00:00 146 28-Feb-2023 23:50:00 120
There are other functions as well that can do this. I prefer accumarray because I’m used to it.
.
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