readcell is filling cell locations with "1x1 missing"
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David Teitge
am 31 Mai 2019
Kommentiert: Stephan Piotrowski
am 21 Jan. 2022
I am using R2109a and it is recommended to use readcell instead of xlsread. Readcell is slower than xlsread and it is returning "1x1 missing" instead of an empty cell when reading an .xlsx file. I don't know what logical I can use to remove these cell locations without brute forcing the problem. Does anyone else know what I can do to fix this?
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Josef Shaoul
am 11 Jan. 2020
The other answers did not work for me. readtable was very slow, and the cellfun(missing...) solution gave empty columns.
The simple, stupid solution is use readcell (faster than xlsread) and just a double loop over the raw cell data to convert <missing> to NaN. That yielded the same result as xlsread.
Would be ven better if the next version would restore the result from xlsread to readcell, because now the cell array that is imported cannot be saved again in an Excel file!
Stephan Piotrowski
am 21 Jan. 2022
@Josef Shaoul I experienced extremely slow readtable, but found that calling it as readtable(input,'basic',true) greatly improved the performance.
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Guillaume
am 4 Jun. 2019
If your data (excluding header) is purely numeric, you'd be better off using readmatrix instead of readcell. If your date is heterogeneous you'd be better off using readtable. The matrix/table will use less memory than a cell array and more crucially make it very easy to remove rows with <missing> entries with rmmissing.
t = rmmissing(readtable(youfile))
With a cell array, rmmissing will only work if the cell array only contain char vectors.
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Jon Martinez
am 4 Jun. 2019
I've had the same problem reading a CSV file and managed to substitute all missing cells with this command:
your_file = readcell(your_path);
your_file(cellfun(@(x) any(ismissing(x)), your_file)) = {''};
The cellfun command will give you a logical array that mantains the structure of the original cell array. Hope it helps.
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