matlab: transform value in CSV column when importing with readmatrix

You may want to use a different approach with textscan. (this is what MATLAB's uiopen-GUI uses if you click on create code).

The problem with readmatrix is that it cannot handle different datatypes. This becomes obvious if you try to concatnate a datetime-vector with a numerical matrix.

So you need to use a talbe, a cell, or split the reading.

function Dat = importfile(filename, startRow, endRow)
%IMPORTFILE Import numeric data from a text file as a matrix.
%   DAT = IMPORTFILE(FILENAME) Reads data from text file FILENAME for the
%   default selection.
%
%   DAT = IMPORTFILE(FILENAME, STARTROW, ENDROW) Reads data from rows
%   STARTROW through ENDROW of text file FILENAME.
%
% Example:
%   Dat = importfile('CSVFILE.csv', 1, 23);
%
%    See also TEXTSCAN.

% Auto-generated by MATLAB on 2020/03/07 21:59:43

%% Initialize variables.
delimiter = ';';
if nargin<=2
    startRow = 1;
    endRow = inf;
end

%% Read columns of data as text:
% For more information, see the TEXTSCAN documentation.
formatSpec = '%s%s%s%s%s%s%[^\n\r]';

%% Open the text file.
fileID = fopen(filename,'r');

%% Read columns of data according to the format.
% This call is based on the structure of the file used to generate this
% code. If an error occurs for a different file, try regenerating the code
% from the Import Tool.
dataArray = textscan(fileID, formatSpec, endRow(1)-startRow(1)+1, 'Delimiter', delimiter, 'TextType', 'string', 'HeaderLines', startRow(1)-1, 'ReturnOnError', false, 'EndOfLine', '\r\n');
for block = 2:length(startRow)
    frewind(fileID);
    dataArrayBlock = textscan(fileID, formatSpec, endRow(block)-startRow(block)+1, 'Delimiter', delimiter, 'TextType', 'string', 'HeaderLines', startRow(block)-1, 'ReturnOnError', false, 'EndOfLine', '\r\n');
    for col=1:length(dataArray)
        dataArray{col} = [dataArray{col};dataArrayBlock{col}];
    end
end

%% Close the text file.
fclose(fileID);

%% Convert the contents of columns containing numeric text to numbers.
% Replace non-numeric text with NaN.
raw = repmat({''},length(dataArray{1}),length(dataArray)-1);
for col = 1:length(dataArray)-1
    raw(1:length(dataArray{col}),col) = mat2cell(dataArray{col}, ones(length(dataArray{col}), 1));
end
numericData = NaN(size(dataArray{1},1),size(dataArray,2));

for col = [2,3,4,5,6]
    % Converts text in the input cell array to numbers. Replaced non-numeric
    % text with NaN.
    rawData = dataArray{col};
    for row=1:size(rawData, 1)
        % Create a regular expression to detect and remove non-numeric prefixes and
        % suffixes.
        regexstr = '(?<prefix>.*?)(?<numbers>([-]*(\d+[\,]*)+[\.]{0,1}\d*[eEdD]{0,1}[-+]*\d*[i]{0,1})|([-]*(\d+[\,]*)*[\.]{1,1}\d+[eEdD]{0,1}[-+]*\d*[i]{0,1}))(?<suffix>.*)';
        try
            result = regexp(rawData(row), regexstr, 'names');
            numbers = result.numbers;

            % Detected commas in non-thousand locations.
            invalidThousandsSeparator = false;
            if numbers.contains(',')
                thousandsRegExp = '^[-/+]*\d+?(\,\d{3})*\.{0,1}\d*$';
                if isempty(regexp(numbers, thousandsRegExp, 'once'))
                    numbers = NaN;
                    invalidThousandsSeparator = true;
                end
            end
            % Convert numeric text to numbers.
            if ~invalidThousandsSeparator
                numbers = textscan(char(strrep(numbers, ',', '')), '%f');
                numericData(row, col) = numbers{1};
                raw{row, col} = numbers{1};
            end
        catch
            raw{row, col} = rawData{row};
        end
    end
end

% Convert the contents of columns with dates to MATLAB datetimes using the
% specified date format.
try
    dates{1} = datetime(dataArray{1}, 'Format', 'dd-MMM-yyyy HH:mm:ss', 'InputFormat', 'dd-MMM-yyyy HH:mm:ss');
catch
    try
        % Handle dates surrounded by quotes
        dataArray{1} = cellfun(@(x) x(2:end-1), dataArray{1}, 'UniformOutput', false);
        dates{1} = datetime(dataArray{1}, 'Format', 'dd-MMM-yyyy HH:mm:ss', 'InputFormat', 'dd-MMM-yyyy HH:mm:ss');
    catch
        dates{1} = repmat(datetime([NaN NaN NaN]), size(dataArray{1}));
    end
end

dates = dates(:,1);

%% Split data into numeric and string columns.
rawNumericColumns = raw(:, [2,3,4,5,6]);

%% Replace non-numeric cells with NaN
R = cellfun(@(x) ~isnumeric(x) && ~islogical(x),rawNumericColumns); % Find non-numeric cells
rawNumericColumns(R) = {NaN}; % Replace non-numeric cells

%% Create output variable
Dat = table;
Dat.date = dates{:, 1};
Dat.a = cell2mat(rawNumericColumns(:, 1));
Dat.b = cell2mat(rawNumericColumns(:, 2));
Dat.c = cell2mat(rawNumericColumns(:, 3));
Dat.d = cell2mat(rawNumericColumns(:, 4));
Dat.e = cell2mat(rawNumericColumns(:, 5));

end

It basically reads everything in as strings (formatSpec = '%s%s%s%s%s%s%[^\n\r]';) and stores it in the cell dataArray. Then it separates the numeric values from other types creating the variable numericData. Then (lines 87-101) it converts the non-numeric date-strings to datetimes

% Convert the contents of columns with dates to MATLAB datetimes using the
% specified date format.
dates{1} = datetime(dataArray{1}, 'Format', 'dd-MMM-yyyy HH:mm:ss','InputFormat', 'dd-MMM-yyyy HH:mm:ss');

Finally, everything is wraped up in a nice table and renamed according to my specifications

%% Create output variable
Dat = table;
Dat.date = dates{:, 1};
Dat.a = cell2mat(rawNumericColumns(:, 1));
Dat.b = cell2mat(rawNumericColumns(:, 2));
Dat.c = cell2mat(rawNumericColumns(:, 3));
Dat.d = cell2mat(rawNumericColumns(:, 4));
Dat.e = cell2mat(rawNumericColumns(:, 5));

I hoped that helped. It memory efficiency is your concern, do the conversion while scanning the csv-file and not as a subsequent step (as the auto-generated function suggests).