Hi everybody,
I am going to use a collection of ~150 .CSV files (comma separated value file) as the input of my training network in MATLAB machine learning .
does anybody have a suggestion that how can I use this collection of .csv files ? is it possible to put them all together in a vector? and if yes, does it going to be fast enough ? especially for further machine learning purpose?
Dear Sajad Saraygord Afshari ,
Look the link, maybe useful.
https://uk.mathworks.com/help/matlab/ref/csvread.html
https://www.mathworks.com/matlabcentral/answers/362333-how-to-import-multiple-csv-files-into-one-and-read-it-from-certain-folder
Regards,
Shafagat
I can use a "for loop" with "csvread" command for it, but it is not efficient for sure!
Dear Sajad Saraygord Afshari ,
Look the link, maybe useful.
https://uk.mathworks.com/help/matlab/ref/csvread.html
https://www.mathworks.com/matlabcentral/answers/362333-how-to-import-multiple-csv-files-into-one-and-read-it-from-certain-folder
Regards,
Shafagat
It seems a datastore can help you: "A datastore allows you to read and process multiple files as a single entity" (http://www.mathworks.com/help/matlab/datastore.html).
Hi Guys,
I just used the following scripts to read the data, and it works perfect. remember that , the file sort in MATLAB is not the same as windows, and so, many times you need to sort the files before using them in next steps. here is my code:
dr=dir('*.csv');
n=length(dr);
d=natsortfiles({dr.name});
data=cell(1,n);
for i=1:n
data{i}=csvread(d{i},1,1);
end
datamat=cell2mat(data);
datavect=reshape(datamat,[],1);
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