How to calculate daily, monthly climatology from time series ?

I have 10year series data with 1min resolution. I want to calculate daily, monthly climatology.

I mean I want to see each month variations over 10yrs.

Ex: Jan-2001+Jan-2002+.......+Jan-2010/10=result

like I want to do for all months and days

Answer 1

[Ameer Hamza]

You can convert your data into timetable and transform it to a different scale using retime function

% generating a random table with daily values
times = datetime('2020-01-01'):days(1):datetime('2020-01-30');
Table = timetable(times', rand(length(times), 1), rand(length(times), 1));

Table_weekly = retime(Table, 'weekly', 'mean'); % calculating weekly average

[Jeevan Kumar Bodaballa]

Thank you for reply but this is not what I am exactly looking.

I want to pick whole January months from whole 10yrs and calculate mean. Like I want to do other months too.

[Ameer Hamza]

The same code will work with some modifications

% generating a random table with daily values
times = datetime('2011-01-01'):days(1):datetime('2019-12-30');
Table = timetable(times', rand(length(times), 1), rand(length(times), 1));
Table_monthly = retime(Table, 'monthly', 'mean'); % calculating weekly average

months_order = month(Table_monthly.Time);
all_month_sum = ...
    cell2mat(splitapply(@(x) {sum(x, 1)}, Table_monthly.Variables, months_order));
all_month_sum(months_order(1:12), :) = all_month_sum; % bringing January to top

This creates random data for 9 years and then sum the values for all years. Final matrix has the of 12 x n, where n is the number of columns of the initial dataset.