convert multidimensional array to a table with multi indexing

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Rami
Rami 2017-4-19
评论： Peter Perkins 2017-4-21
I have a multidimensional matrix say M such that
M=rand(5,4,3,2)
where the 5 rows stand for say last names of customers and the 4 columns stand for their {age, weight, activities, happiness level}, while the other 3 multi-matrix stands for years {1999,2003,2009}, while 2 stand for countries {A, and B}
How could i transfer this matrix to be a table with multi-index?
Thank you very much

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回答（2 个）

Sebastian Castro
Sebastian Castro 2017-4-20
The array2table function wants your matrix to be 2-dimensional (or m-by-n, as they say in the documentation).
One thing you could try is use reshape as follows:
M = rand(5,4,3,2);
M2 = reshape(M,[5, 4*3*2])
This will give you a 5-by-24 matrix, but you lose all the multi-indexing capabilities. Each column would have to be given a name that indicates which year and country you want.
Another approach is to keep some of the nesting. See below. The squeeze function is used such that each table element is 3-D instead of 4-D:
T = table;
T.Age = squeeze(M(:,1,:,:));
T.Weight = squeeze(M(:,2,:,:));
T.Activities = squeeze(M(:,3,:,:));
T.Happiness = squeeze(M(:,4,:,:));
So in this case if you wanted customer 4's age in 2003, country A, you'd say:
thisGuysAge = T.Age(4,2,1);
You could get real fancy with this, e.g.:
years = [1993 2003 2009];
countries = {'A','B'};
thisGuysAge = T.Age(4 , years==2003 , strcmp(countries,'A'))
... and so on. Ultimately it's a trade-off between having a 2-D table where you have to figure out how to distinguish between years and ages vs. keeping some of the multidimensionality and having the ability to index in.
Sebastian
  1 个评论
Peter Perkins
Peter Perkins 2017-4-21
It's also possible to take this one step further and make each variable itself a table.
>> years = {'y1999' 'y2003' 'y2009'};
>> T.Age = table(squeeze(T.Age(:,1,:)),squeeze(T.Age(:,2,:)),squeeze(T.Age(:,3,:)), ...
'VariableNames',years);
>> T.Weight = table(squeeze(T.Weight(:,1,:)),squeeze(T.Weight(:,2,:)),squeeze(T.Weight(:,3,:)), ...
'VariableNames',years);
>> T.Activities = table(squeeze(T.Activities(:,1,:)),squeeze(T.Activities(:,2,:)),squeeze(T.Activities(:,3,:)), ...
'VariableNames',years);
>> T.Happiness = table(squeeze(T.Happiness(:,1,:)),squeeze(T.Happiness(:,2,:)),squeeze(T.Happiness(:,3,:)), ...
'VariableNames',years);
>> T
T =
5×4 table
Age Weight Activities Happiness
___________ ___________ ___________ ___________
[1x3 table] [1x3 table] [1x3 table] [1x3 table]
[1x3 table] [1x3 table] [1x3 table] [1x3 table]
[1x3 table] [1x3 table] [1x3 table] [1x3 table]
[1x3 table] [1x3 table] [1x3 table] [1x3 table]
[1x3 table] [1x3 table] [1x3 table] [1x3 table]
The display for that is not great, but the subscripting works as you might hope to give you named indexing one level deeper:
>> T.Age
ans =
5×3 table
y1999 y2003 y2009
__________________ __________________ ___________________
0.02193 0.86234 0.7663 0.74618 0.47524 0.85337
0.80828 0.8964 0.7513 0.11749 0.80532 0.39812
0.17921 0.18901 0.13886 0.50902 0.53078 0.11549
0.16539 0.66072 0.34932 0.16883 0.22731 0.080281
0.1816 0.94123 0.15134 0.83111 0.70948 0.36047
>> T.Age.y1999
ans =
0.02193 0.86234
0.80828 0.8964
0.17921 0.18901
0.16539 0.66072
0.1816 0.94123
>> T.Age.y1999(1,1)
ans =
0.02193
And then of course you can make T.Age.y1999, etc., themselves each a table. You'd have three levels of tables, and at each you'd subscript by measurement, year, and country, respectively.
The code above gets pretty tedious, but I've typed it out like that only to make it more understandable. You could easily write loops to do it all.

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Peter Perkins
Peter Perkins 2017-4-21
Another possibility is to flatten out the data. You may have the N-D organization on purpose. but here's one way to flatten the data out.
>> M = reshape(1:120,[5 4 3 2]);
>> T = array2table(M(:,:));
>> T = stack(T,{1:4:24 2:4:24 3:4:24 4:4:24}, ...
'IndexVariableName','Subject', ...
'NewDataVariableName',{'Age' 'Weight' 'Activities' 'Happiness'});
>> T.Subject = categorical(repelem({'Subject1'; 'Subject2'; 'Subject3'; 'Subject4'; 'Subject5'},6));
>> T.Year = categorical(repmat(repmat({'y1999'; 'y2003'; 'y2009'},2,1),5,1));
>> T.Country = categorical(repmat(repelem({'CountryA'; 'CountryB'},3),5,1));
>> T = T(:,[1 6 7 2:5])
T =
30×7 table
Subject Year Country Age Weight Activities Happiness
________ _____ ________ ___ ______ __________ _________
Subject1 y1999 CountryA 1 6 11 16
Subject1 y2003 CountryA 21 26 31 36
Subject1 y2009 CountryA 41 46 51 56
Subject1 y1999 CountryB 61 66 71 76
Subject1 y2003 CountryB 81 86 91 96
Subject1 y2009 CountryB 101 106 111 116
Subject2 y1999 CountryA 2 7 12 17
Subject2 y2003 CountryA 22 27 32 37
Subject2 y2009 CountryA 42 47 52 57
Subject2 y1999 CountryB 62 67 72 77
Subject2 y2003 CountryB 82 87 92 97
Subject2 y2009 CountryB 102 107 112 117
Subject3 y1999 CountryA 3 8 13 18
Subject3 y2003 CountryA 23 28 33 38
Subject3 y2009 CountryA 43 48 53 58
Subject3 y1999 CountryB 63 68 73 78
Subject3 y2003 CountryB 83 88 93 98
Subject3 y2009 CountryB 103 108 113 118
Subject4 y1999 CountryA 4 9 14 19
Subject4 y2003 CountryA 24 29 34 39
Subject4 y2009 CountryA 44 49 54 59
Subject4 y1999 CountryB 64 69 74 79
Subject4 y2003 CountryB 84 89 94 99
Subject4 y2009 CountryB 104 109 114 119
Subject5 y1999 CountryA 5 10 15 20
Subject5 y2003 CountryA 25 30 35 40
Subject5 y2009 CountryA 45 50 55 60
Subject5 y1999 CountryB 65 70 75 80
Subject5 y2003 CountryB 85 90 95 100
Subject5 y2009 CountryB 105 110 115 120

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