Performance: readTable versus xlsread

Dear Community,

I am reading the contents of an Excel Workbook (.xlsx) file. It's a pretty large, but not crazy file (approximately 26k rows-by-24 columns; 3MB). The data is a mixture of a text header (row 1) and the rest is a mixture of numbers and strings.

Until now, I've been using xlsread to process this file. According to the MATLAB documentation, xlsread is not recommended and I should consider readtable or readcell instead:

"The readtable, readmatrix, and readcell functions have these advantages over the xlsread function: Better cross-platform support and performance..."

In MATLAB 2019a for my Excel file, xlsread takes about 1.2 seconds to get the output; readtable takes about 12 seconds; readcell takes about 42 seconds.

It appears to me that xlsread is superior to the other two methods when it comes to speed. Hence my question: What is meant in the documentation by "Better cross-platform support and performance"? What is this performance measured relative to? I appreciate that readtable and readcell have various other advantages, so I understand their use cases. I'm wondering if there's anything obvious that I'm missing which could improve the performance?

I'm calling the methods in a very simple fashion:

[~, ~, csvData] = xlsread(filename);
csvData = readtable(filename);
csvData = readcell(filename);

Thanks,

Louis

[Jeremy Hughes]

Interested if you've tried this is a recent MATLAB release. Or if you have a file that is running slowly, attach it. Then someone might be able to provide a better answer.

Answer 1

[Abdolkarim Mohammadi]

I don't know about the exact thing you mentioned, but I have experienced that when reading many matrixes from Excel (hence many calls to xlsread() or readmatrix()), the file with readmatrix() runs significantly faster than the same file but with xlsread().

[fsgeek]

That sounds promising. Unfortunately, I can't use readmatrix because my data contains non-numeric cells.