How to find mean&stdev of different unique IDs in given table

Hi,

I want to calculate mean and stdv of the below table based on column1 (the column1 data may vary)

Now, I have the following different IDs in column1:HTD1,HTD2,HTD4,HTD6,HTD9,HTD12,HTD13 (because I knew now, but they may vary). Please someone kindly help how can I find the mean &stdev of different unique IDs in column1. And how can ensure which result is for which unique ID(like here: HTD1,HTD2,HTD4,HTD6,HTD9,HTD12,HTD13).

HTD1  Recipe1      0.1
HTD2  Recipe11    0.8
HTD1  Recipe2      1.1
HTD4  Recipe25    0.9
HTD2  Recipe22    2.0
HTD6  Recipe43    2.4
HTD1  Recipe8      1.4
HTD6  Recipe44    2.0
HTD9  Recipe56    0.9
HTD2  Recipe19    0.7
HTD1  Recipe8      1.5
HTD12  Recipe15    0.6
HTD13  Recipe91    1.1
HTD2  Recipe11    2.2
HTD1  Recipe2      1.2
HTD4  Recipe25    1.4
HTD6  Recipe44    0.1
HTD9  Recipe56    0.3
HTD2  Recipe19    1.4
HTD1  Recipe8      1.2 
HTD12  Recipe15    0.6
HTD6  Recipe44    0.1
HTD6  Recipe44    0.1
HTD2  Recipe4      0.6

Many many thanks in advance.

[Image Analyst]

Make it easy for us to help you and give the code where you created the table. And, have you looked at unique() and ismember()?

Answer 1

[Guillaume]

Since what you've shown is not how matlab displays a http://www.mathworks.com/help/releases/R2014b/matlab/tables.html table>, I assume what you've got is not truly a table but most likely a cell array. As per Image Analyst comment, it's always a good idea to show how you create your data (or use proper matlab syntax).

So, given:

c = {'HTD1'  'Recipe1'     0.1
     'HTD2'  'Recipe11'    0.8
     'HTD1'  'Recipe2'     1.1
     'HTD4'  'Recipe25'    0.9
     'HTD2'  'Recipe22'    2.0
     'HTD6'  'Recipe43'    2.4
     'HTD1'  'Recipe8'     1.4
     'HTD6'  'Recipe44'    2.0
     'HTD9'  'Recipe56'    0.9
     'HTD2'  'Recipe19'    0.7
     'HTD1'  'Recipe8'     1.5
     'HTD12'  'Recipe15'    0.6
     'HTD13'  'Recipe91'    1.1
     'HTD2'  'Recipe11'    2.2
     'HTD1'  'Recipe2'     1.2
     'HTD4'  'Recipe25'    1.4
     'HTD6'  'Recipe44'    0.1
     'HTD9'  'Recipe56'    0.3
     'HTD2'  'Recipe19'    1.4
     'HTD1'  'Recipe8'     1.2 
     'HTD12'  'Recipe15'    0.6
     'HTD6'  'Recipe44'    0.1
     'HTD6'  'Recipe44'    0.1
     'HTD2'  'Recipe4'     0.6}

Use unique to get the unique IDs and their location:

[ids, ~, rows] = unique(c(:, 1));

Use accumarray with these rows to calculate the standard deviation and mean of column 3:

means = accumarray(rows, cell2mat(c(:, 3)), [], @mean);
stddevs = accumarray(rows, cell2mat(c(:, 3)), [], @std);
output = [ids num2cell([means stddevs])]