# How can i compute the mean of specific number of table rows?

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Ioannis Tsikriteas on 9 Aug 2017
Commented: Cong Ba on 10 Aug 2017
Hi, I have a large amount of table data which is divided by date and time....to be more specific i have data that is per 10 minutes and i want to compute the mean of them per hour! In other words, i want ot compute the mean of my data per 10 rows until my data is finished! Is this possible and if yes....which command should i use?

Cong Ba on 9 Aug 2017
Try reshape:
a = randn(100,1); % assume this is the column you have
b = reshape(a,[10,10]); % reshape it so each column has 10 rows
avg = mean(b);
Ioannis Tsikriteas on 10 Aug 2017
Edited: Ioannis Tsikriteas on 10 Aug 2017
When i try the reshape command i get the following message: Error using tabular/reshape (line 150) Undefined function 'reshape' for input arguments of type 'table'.
To be more clear isend a pic of the shape of my data tables
Cong Ba on 10 Aug 2017
Andrei is using the timetable function which may better suit your need (you essentially have a time series). But if you want to manipulate data in matrix form (my code works for matrix form), you can try this function: table2array

Andrei Bobrov on 9 Aug 2017
n = 278984;
t = minutes(10*(1:n)');
D = randi(255,n,2); % Let D - your data (278984 x 2)
TT = timetable(t,D(:,1),D(:,2));
TT_out = retime(TT,'hourly','mean');
Ioannis Tsikriteas on 10 Aug 2017
I am sorry but i didn't understand the concept of these commands.
Mine data are already ona a table 278984x2 and has the following shape:
I am searching a way to compute the mean between the fifth and the eleventh row for example in order to have my data per hour, not per 10 minutes
Andrei Bobrov on 10 Aug 2017
Edited: Andrei Bobrov on 10 Aug 2017
a.x_10_double = [a.x_10_{:}]';
TT = table2timetable(a(:,[1,3]),'RowTimes','x08_Jul_100_10_00');
TT_out = retime(TT,'hourly','mean');
or
a2 = table(a{:,1},[a{:,2}{:}]','v',{'datetime','x_10_double'})
a2.groups = hour(a2{:,1});
a_out = varfun(@mean,a2,'Group','groups');

Peter Perkins on 10 Aug 2017
Add a grouping variable to your table and use varfun. Something like
n = ceil(height(t)/10);
g = repelem(1:n,10)';
t.Group = g(1:height(t));
t.groupMeans = varfun(@mean,t,'GroupingVariable','Group')