Add a useful package (from Source forge) for octave

[CreaPhase.git] / octave_packages / dataframe-0.9.1 / @dataframe / summary.m

diff --git a/octave_packages/dataframe-0.9.1/@dataframe/summary.m b/octave_packages/dataframe-0.9.1/@dataframe/summary.m
new file mode 100644 (file)
index 0000000..1a82492
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+++ b/octave_packages/dataframe-0.9.1/@dataframe/summary.m
@@ -0,0 +1,86 @@
+function resu = summary(df)
+  %# function resu = summary(df)
+  %# This function prints a nice summary of a dataframe, on a
+  %# colum-by-column basis. For continuous varaibles, returns basic
+  %# statistics; for discrete one (char, factors, ...), returns the
+  %# occurence count for each element.
+
+  %% Copyright (C) 2009-2012 Pascal Dupuis <Pascal.Dupuis@uclouvain.be>
+  %%
+  %% This file is part of Octave.
+  %%
+  %% Octave is free software; you can redistribute it and/or
+  %% modify it under the terms of the GNU General Public
+  %% License as published by the Free Software Foundation;
+  %% either version 2, or (at your option) any later version.
+  %%
+  %% Octave is distributed in the hope that it will be useful,
+  %% but WITHOUT ANY WARRANTY; without even the implied
+  %% warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
+  %% PURPOSE.  See the GNU General Public License for more
+  %% details.
+  %%
+  %% You should have received a copy of the GNU General Public
+  %% License along with Octave; see the file COPYING.  If not,
+  %% write to the Free Software Foundation, 51 Franklin Street -
+  %% Fifth Floor, Boston, MA 02110-1301, USA.
+  
+  %#
+  %# $Id: summary.m 9585 2012-02-05 15:32:46Z cdemills $
+  %#
+
+  dummy = df._type; resu = [];
+  
+  for indi = 1:length(dummy),
+    switch dummy{indi}
+      case {'char' 'factor'}
+       [sval, sidxi, sidxj] = unique(df._data{:, indi});
+       %# compute their occurences
+       sidxj = hist(sidxj, min(sidxj):max(sidxj));
+       %# generate a column with unique values
+       resuR = strjust(char(regexp(disp(sval), '\S.*', 'match', ...
+                                   'dotexceptnewline')), 'right');
+       resuR = horzcat(resuR, repmat(':', size(resuR, 1), 1),
+                       strjust(char(regexp(disp(sidxj.'), '\b.*', 'match', ...
+                                           'dotexceptnewline')), ...
+                               'right'));
+       %# now put the name above all
+       resuR = strjust([deblank(df._name{1, 2}(indi, :)); resuR], 'right');
+       resuR = horzcat(resuR, repmat(' ', size(resuR, 1), 1));
+       resu = horzcat_pad(resu, resuR);
+       
+      otherwise
+       s = statistics(df._data{:, indi});
+       s = s([1:3 6 4:5]);
+       %# generate a column with name and fields name
+       resuR = strjust([deblank(df._name{1, 2}{indi, :}); 
+                        "Min.   :"; "1st Qu.:";
+                        "Median :"; "Mean   :";
+                        "3rd Qu.:"; "Max.   :"], 'right');
+       %# generate a column with a blank line and the values
+       resuR = horzcat(resuR, repmat(' ', size(resuR, 1), 1),
+                       strjust(char(' ', regexp(disp(s), '\S.*', 'match', ...
+                                                'dotexceptnewline')), 'right'),...
+                       repmat(' ', size(resuR, 1), 1));
+       resu = horzcat_pad(resu, resuR);
+        
+    endswitch
+  endfor
+  
+endfunction
+
+
+function resu = horzcat_pad(A, B)
+  %# small auxiliary function to cat horizontally tables of different height
+  dx = size(A, 1) - size(B, 1);
+  
+  if dx < 0,
+    %# pad A
+    A = strvcat(A, repmat(' ', -dx, size(A, 2)));
+  elseif dx > 0
+    B = strvcat(B, repmat(' ', dx, size(B, 2)));
+  endif
+
+  resu =  horzcat(A, B);
+
+endfunction