Rehsaping Data Table to new format
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Hi, I have a data table that exists like:
[date] [field] [data]
1/1/2017 A 1
1/2/2017 A 2
1/3/2017 A 3
1/1/2017 B 3
1/2/2017 B 2
1/3/2017 B 1
1/1/2017 C 4
1/2/2017 C 5
1/3/2017 C 6
and i want to reshape the data to be like this:
[Date] [A] [B] [C]
1/1/2017 1 3 4
1/2/2017 2 2 5
1/3/2017 3 1 6
so that each unique value in fields becomes a new field name in the new table.
I saw this conversion done in a tutorial the other day, but cant recall how it was done at all, thanks for any input in advance!
Matt
采纳的回答
Peter Perkins
2017-4-7
I think you are looking for unstack:
>> t = cell2table( ...
{'1/1/2017', 'A', 1; ...
'1/2/2017', 'A', 2; ...
'1/3/2017', 'A', 3; ...
'1/1/2017', 'B', 3; ...
'1/2/2017', 'B', 2; ...
'1/3/2017', 'B', 1; ...
'1/1/2017', 'C', 4; ...
'1/2/2017', 'C', 5; ...
'1/3/2017', 'C', 6},'VariableNames',{'date' 'field' 'data'});
>> t.date = datetime(t.date,'InputFormat','MM/dd/yyy');
>> t.field = categorical(t.field)
t =
9×3 table
date field data
___________ _____ ____
01-Jan-2017 A 1
02-Jan-2017 A 2
03-Jan-2017 A 3
01-Jan-2017 B 3
02-Jan-2017 B 2
03-Jan-2017 B 1
01-Jan-2017 C 4
02-Jan-2017 C 5
03-Jan-2017 C 6
>> t2 = unstack(t,'data','field')
t2 =
3×4 table
date A B C
___________ _ _ _
01-Jan-2017 1 3 4
02-Jan-2017 2 2 5
03-Jan-2017 3 1 6
更多回答（2 个）
Steven Lord
2017-4-7
0 个投票
If your data is stored in a table or timetable, use unstack. The first example on that documentation page is pretty close to the exact scenario you gave, so it should be easy to adapt for your needs.
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