MATLAB-使用具有多个类别的accumarray吗? [英] MATLAB - Working with accumarray with multiple categories?

问题描述

我正在跟进我的问题此处，其中有一个完美的解决方案完全可以满足我的要求.但是我想知道如何应用这种方法，或者做类似的事情，如果我将有两个以上的响应，而不是是/否，那么例如是/否.或将其推广到3个以上的响应中.

I am asking a follow-up my question here, in which there was a perfect solution that did exactly what I wanted. But I'm wondering how to apply this method, or do something similar, if instead of yes/no as possible responses, I would have more than 2 responses, so yes/no/maybe, for example. Or how it would generalize to 3+ responses.

这是答案，重新格式化为我的问题:

This is the answer, reformatted as my question:

假设我的数据如下:

responses = categorical(randi(3,1250,1),[1 2 3],{'no','yes','maybe'});
race = categorical(randi(5,1250,1),1:5,{'Asian','Black','BHispanic','White','WHispanic'});

我想对是/否数据做同样的事情，但是用3种或更多的可能性来做.这将最终无法正常工作:

I would like to go through and do the same thing with my yes/no data, but do this with 3 possibilities, or more. And this will not end up working anymore:

% convert everything to numeric:
yn = double(responses); 
rac = double(race);
% caluculate all frequencies:
data = accumarray(rac,yn-1);
data(:,2) = accumarray(rac,1)-data;
% get the categories names:
races = categories(race);   
answers = categories(responses);
% plotting:
bar(data,0.4,'stacked');
ax = gca;
ax.XTickLabel = races; % set the x-axis ticks to the race names
legend(answers) % add a legend for the colors
colormap(lines(3)) % use nicer colors (close to your example)
ylabel('YES/NO/MAYBE')% set the y-axis label
% some other minor fixes:
box off
ax.YGrid = 'on';

我不确定是否甚至可以使用accumarray方法来执行此操作，因为根据我的理解，将其与3种可能的响应一起使用是没有意义的.我也想将其概括为n个可能的响应.

I'm not sure if there is even a way to use the accumarray method to do this, as it doesn't make sense from my understanding to use this with 3 possible responses. I'd like to generalize it to n possible responses too.

更新:我目前正在研究交叉表功能，到目前为止我才发现它！我认为这可能是我要寻找的功能.

UPDATE: I'm currently investigating the crosstab feature which I didn't find at all until now! I think this may be the feature I'm looking for.

推荐答案

以下是通用版本:

% the data (with even more categories):
yesno = categorical(randi(4,1250,1),1:4,{'no','yes','maybe','don''t know'});
race = categorical(randi(5,1250,1),1:5,{'Asian','Black','BHispanic','White','WHispanic'});
% convert everything to numeric:
yn = double(yesno); 
rac = double(race);
% caluculate all frequencies:
data = accumarray([rac yn],1);
% get the categories names:
races = categories(race);   
answers = categories(yesno);
% plotting:
bar(data,0.4,'stacked');
ax = gca;
ax.XTickLabel = races; % set the x-axis ticks to the race names
legend(answers) % add a legend for the colors
colormap(lines(numel(answers))) % use pretier colors
ylabel('YES/NO')% set the y-axis lable
% some other minor fixes:
box off
ax.YGrid = 'on';

结果:

在表格中:

T = array2table(data.','VariableNames',races,'RowNames',answers)

输出:

T = 
                  Asian    Black    BHispanic    White    WHispanic
                  _____    _____    _________    _____    _________
    no            58       72       69           66       62       
    yes           58       53       72           54       58       
    maybe         63       62       67           62       61   
    don't know    58       57       66           58       74      

---

如前所述，您可以将crosstab用于同一任务. crosstab(rac,yn)将为您提供与accumarray([rac yn],1)相同的结果.我认为accumarray更快，尽管我没有检查.

---

As you already mentioned, you can use crosstab for the same task. crosstab(rac,yn) will give you the same result as accumarray([rac yn],1). I think accumarray is faster, though I didn't check it.

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