convert categorical to numeric (2024)

I have the same problem, and the help file.... does not help at all

My data is categorical because the importdata chose that for it, I can force but then if I import new data and don't force it to numerical, my processing will stop working. I'm running a script so I can put a conversion there -> automate not rely on human memory!

In particular I have 160,000 lines of data in a table, one of 46 fields is an odo reading. This has converted to categorical, with 16983 categories - so might be more efficient, fair enough. But now I want to plot data against odo, so I need numerical. example subset:

>> catdata

ans = 1×8 categorical array

37241 37364 37099 4264 6339 38209 38070 16777215

So the original numbers are NOT lost, but are coded in the categories:

>> catcats=categories(catdata);

>> length(catcats)

ans = 16983

As noted above, double () gives the index not the value

>> double(catdata)

ans =

10880 10902 10858 11593 13789 11022 11004 4659

>> catcats(4659)

ans = 1×1 cell array

{'16777215'}

But cell2mat gives you a string not a number:

>> cell2mat(catcats(4659))

ans = '16777215'

So you then need to convert again using str2num (why no cell2num? There is a num2cell):

>> str2num(cell2mat(catcats(4659)))

ans = 16777215

So this works for one item, but when I use the 8 element data with the resulting strings being different length, it fails

>> catcats(double(catdata))

ans = 8×1 cell array

{'37241' }

{'37364' }

{'37099' }

{'4264' }

{'6339' }

{'38209' }

{'38070' }

{'16777215'}

>> cell2mat(catcats(double(catdata)))

Error using cat

Dimensions of matrices being concatenated are not consistent.

Error in cell2mat (line 83)

m{n} = cat(1,c{:,n});

This seems like way more difficult than it should be.

The fundamental problem is that your numeric data are being read in as categorical. I don't have your file, so I can't tell why that is, but I recommend you use detectimportoptions, and set the type, and use that in calls to readtable to read in all of your other data.

Thanks.

I've come to the conclusion that would have been easiest, although I've developed an effective though crude workaround.

vfdbdata.DD01km is my categorical data array (from a table of data)

So this is run before the main processing, the numeric data can then be extracted as required by

The max ensures that 'undefined' values are processed without throwing an error (they give a NaN after translation to double, which causes a subscript error), I also have some code to process specific values that can occur (hence the use of a temporary variable).