Retain dummy variable labels from converting categorical to dummyvar
Hi there,
I have 19 categorical columns which I have converted into being a number for each category. However, I want to increase the number of columns so that I have a dummy for each category. What I find is that I have no idea where the dummy variables have gone, which I need to make an interpretable solution e.g. if a user is from Thailand or not, that variable is significant in a logistic regression.
Here is my code:
%categoricalnbs is the number converted version for all the categorical
%variables. Some columns in that table have categories 1-200, some just
%have categories 1 to 20.categoricalnbsarray = table2array(categoricalnbs);% categoricalnbsarray = table2array(finalnbs(:,[9:26,28]));
%finalnbs keeps the actual category names, which I thought could help with
%generating the column labels for the dummyvars, but using that line
%doesn't help.[~, ~, ugroupA] = unique(categoricalnbsarray(:,2));
dummyvars=dummyvar(ugroupA);
array2table(dummyvars);
This increases the columns in categoricalnbs from 19 to 200, and retains the same number of rows. But how do I interpret the output…
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I wrote a function that does this, here you go:
function Tdummy = dummytable(T)
% Tdummy = dummytable(T) - convert categorical variables in table to dummy
% variables
%
% This function takes the categorical variables in a table and converts
% them to separate dummy variables with intelligent names. This way they
% can be used in the Classification Learner App and the variable names make
% sense for feature selection, etc.
%
% Usage:
%
% Tdummy = dummytable(T)
%
% Inputs:
%
% T: Table with categoricals or categorical variable
%
% Outputs:
%
% Tdummy: T with categorical variables turned into dummy variables with
% intelligent names
%
% Example:
%
% % Simple Table
% T = table(rand(10,1),categorical(cellstr('rbbgbgbbgr'.')),...
% 'VariableNames',{'Percent','Color'});
% disp(T)
%
% % Turn it into a dummy table
% Tdummy = dummytable(T);
% disp(Tdummy)
%
% See Also: dummyvar, table, categorical, classificationLearner% Copyright 2015 The MathWorks, Inc.
% Sean de Wolski Apr 13, 2014
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