Fastest Way of Opening and Reading .csv Files (Currently using xlsread)

147 vues (au cours des 30 derniers jours)
Ibro Tutic
Ibro Tutic le 23 Mai 2016
Commenté : Walter Roberson le 25 Août 2020
I am currently trying to convert 100,000+ csv files (all the same size, with the same data structuring on the inside) to mat files, and I am running into the issue that it takes an extremely long time, and sometimes Excel stops responding. Are there any other functions that could cut down on the read time of these .csv files?
I read something about trying the COM server that runs Excel, but I am not sure how to implement it. Any thoughts?

Réponse acceptée

Kirby Fears
Kirby Fears le 23 Mai 2016
Modifié(e) : Kirby Fears le 23 Mai 2016
Thankfully, you don't need to interact with Excel to read csv files. You can use textscan to read csv files quickly.
I wrote a function called delimread that utilizes textscan with automatic parameters. It might be easier than learning how to parameterize textscan.

Plus de réponses (3)

Todd Leonhardt
Todd Leonhardt le 23 Mai 2016

Jeremy Hughes
Jeremy Hughes le 23 Août 2017
Since you have multiple files, you may want to consider using datastore. (Since R2014b)
In many cases, you can just use the following pattern to read a large collection of files,
ds = datastore('folder/containing/your/files')
while(hasdata(ds))
t = read(ds)
% do stuff to t.
end
Hope this helps,
Jeremy

TastyPastry
TastyPastry le 23 Mai 2016
There's a function csvread() which only works on numeric data.
The other way you can do it is to use textscan(). Both of those methods should be faster than xlsread() since xlsread() uses Excel, which is pretty slow.

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by