how to expand the date matrix?
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Hi
I need your help.
I have a csv file with date minimum and date maximum in the last 2 columns. I'd like to expand the date column such that each column is one date. For example, below first is my data, column 3-4 is date min ( Aug 1 2019) and date max (Sept 1 2019). From this matrix, I'd like to expand the matrix to the 2nd figure with 30 columns ( from Aug 1 2019-Aug 2 2019 to Sept 1 2019). How to do it? Thanks
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Answers (2)
Peter Perkins
on 28 Jul 2021
roudan, this question doesn't seem to make any sense. For one thing, it doesn't seem useful that you have a column whose header is 8/1/2019, and all of whose values are 8/1/2019. Same for all the other columns. For another, you say Aug 1 to Sep 1, but you example doesn't even show that.
You are also showing only Excel. If you are asking about how to do this in Excel, you are in the wrong place.
In any case, I suggest you use readtable to import your spreadsheet into a table. Your spreadsheet has two header rows, I have no idea what will actually happen but you will have to sort that out yourself. At that point, you have a table that looks somethign like this:
>> t = table([1;2;3],[4;5;6],datetime(2019,8,[1;1;1]),datetime(2019,9,[1;1;1]))
t =
3×4 table
Var1 Var2 Var3 Var4
____ ____ ___________ ___________
1 4 01-Aug-2019 01-Sep-2019
2 5 01-Aug-2019 01-Sep-2019
3 6 01-Aug-2019 01-Sep-2019
Then do something like this:
>> Dates = t.Var3 + caldays(0:5)
Dates =
3×6 datetime array
01-Aug-2019 02-Aug-2019 03-Aug-2019 04-Aug-2019 05-Aug-2019 06-Aug-2019
01-Aug-2019 02-Aug-2019 03-Aug-2019 04-Aug-2019 05-Aug-2019 06-Aug-2019
01-Aug-2019 02-Aug-2019 03-Aug-2019 04-Aug-2019 05-Aug-2019 06-Aug-2019
>> t = [t(:,1:2) array2table(Dates)]
t =
3×8 table
Var1 Var2 Dates1 Dates2 Dates3 Dates4 Dates5 Dates6
____ ____ ___________ ___________ ___________ ___________ ___________ ___________
1 4 01-Aug-2019 02-Aug-2019 03-Aug-2019 04-Aug-2019 05-Aug-2019 06-Aug-2019
2 5 01-Aug-2019 02-Aug-2019 03-Aug-2019 04-Aug-2019 05-Aug-2019 06-Aug-2019
3 6 01-Aug-2019 02-Aug-2019 03-Aug-2019 04-Aug-2019 05-Aug-2019 06-Aug-2019
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