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Grouping data by value

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Nurul Ain Basirah Zakaria
Nurul Ain Basirah Zakaria 2021 年 2 月 8 日
回答済み: Walter Roberson 2021 年 2 月 8 日
Hi. I have 432x1 data. I need to grouping the data.
for example;
-0.989088822111364
-1.16881053159657
-0.687960193675098
0.609028518151482
0.853112207247799
1.09867863373770
0.325581735572437
-0.358624505229866
-0.116184636997357
-1.12249570113502
-0.878711918410750
-0.843582079603111
-0.763107095944730
-0.963235098445007
-1.36135857090159
-1.93513836539865
-1.53179202986538
-1.24445835422832
0.643855927191538
0.506078478817649
1.10211477120999
0.119654919704736
-0.186087379373470
0.208608204079503
0.542441939121425
1.09907331469601
0.595582967612814
0.605674642059506
-0.0429774937224157
How can I assign them to groups such as:
moderate= -1.00 to -1.49
severe= -1.50 to -1.99

採用された回答

KSSV
KSSV 2021 年 2 月 8 日
Let x be your data. Create arespective y-value which denotes grouping.
y = zeros(size(x)) ;
% get values -1.00 to -1.49
idx = x >= -1 && x < -1.49 ;
y(idx) = 1 ; % say one stand for moderate
% get values between -1.50 and -1.99
idx = x >= -1.50 && x < -1.99 ;
y(idx) = 2 ; % say two stand for

その他の回答 (1 件)

Walter Roberson
Walter Roberson 2021 年 2 月 8 日
discretize() with boundaries and 'categorical' and a list of category names.
data = [
-0.989088822111364
-1.16881053159657
-0.687960193675098
0.609028518151482
0.853112207247799
1.09867863373770
0.325581735572437
-0.358624505229866
-0.116184636997357
-1.12249570113502
-0.878711918410750
-0.843582079603111
-0.763107095944730
-0.963235098445007
-1.36135857090159
-1.93513836539865
-1.53179202986538
-1.24445835422832
0.643855927191538
0.506078478817649
1.10211477120999
0.119654919704736
-0.186087379373470
0.208608204079503
0.542441939121425
1.09907331469601
0.595582967612814
0.605674642059506
-0.0429774937224157];
cats = discretize(data, [-1.99, -1.50, -1, 1, 1.5, 1.99], 'categorical', {'severe', 'moderate', 'nomimal', 'good', 'excellent'})
cats = 29×1 categorical array
nomimal moderate nomimal nomimal nomimal good nomimal nomimal nomimal moderate nomimal nomimal nomimal nomimal moderate severe severe moderate nomimal nomimal good nomimal nomimal nomimal nomimal good nomimal nomimal nomimal

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