Table to Array conversion using a for loop
2 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
Ashfaq Ahmed
el 11 de Jul. de 2022
Comentada: Ashfaq Ahmed
el 14 de Jul. de 2022
Hi! Is there a way I can do this operation within a for loop?
load 'temps-2021-11-16.mat'
temps_2021_11_16 = table2array(data(:,:));
load 'temps-2021-10-31.mat'
temps_2021_10_31 = table2array(data(:,:));
load 'temps-2021-10-15.mat'
temps_2021_10_15 = table2array(data(:,:));
load 'temps-2021-09-13.mat'
temps_2021_09_13 = table2array(data(:,:));
load 'temps-2021-09-29.mat'
temps_2021_09_29 = table2array(data(:,:));
load 'temps-2021-08-12.mat'
temps_2021_08_12 = table2array(data(:,:));
load 'temps-2021-07-27.mat'
temps_2021_07_27 = table2array(data(:,:));
load 'temps-2021-04-06.mat'
temps_2021_04_06 = table2array(data(:,:));
load 'temps-2021-03-21.mat'
temps_2021_03_21 = table2array(data(:,:));
load 'temps-2021-03-05.mat'
temps_2021_03_05 = table2array(data(:,:));
load 'temps-2021-02-17.mat'
temps_2021_02_17 = table2array(data(:,:));
Thank you so much!
1 comentario
Stephen23
el 11 de Jul. de 2022
Editada: Stephen23
el 11 de Jul. de 2022
temps_2021_02_17 = ..
% ^^^^^^^^^^ do not force meta-data into variable names
unless you really want to force yourself into writing slow, complex, inefficient, obfuscated, insecure, buggy code that is hard to debug:
Those files are so neatly designed with one variable name (i.e. 'data'), it really would be such a shame to awkwardly force meta-data into variable names. Indexing is simpler and much more efficient.
Respuesta aceptada
Jon
el 11 de Jul. de 2022
Editada: Jon
el 11 de Jul. de 2022
I agree with @Stephen23 comments about not using dynamically named variables, here's another approach, in which you store all of the data in a single table. You can then easily retrieve data corresponding to a particular date, as shown in the end of the example code,
% get list of relevant data files
list = dir('temps-*.mat')
% loop through data files saving data into tables
tableCell = cell(numel(list),1); % cell array to temporarily hold individual tables
for k = 1:numel(list)
load(list(k).name) % load the table
% find number of rows in the table
numRows = size(data,1);
% add new first column to table with date corresponding to source file name
[~,name] = fileparts(list(k).name)
date = datetime(name(7:end))
dateColumn = table(repmat(date,numRows,1),'VariableNames',{'date'});
data = [dateColumn data]
% put table into temporary cell array
tableCell{k}= data;
end
% concatenate table to make overall table
dataTable = vertcat(tableCell{:})
% now if for example you want an array of data corresponding to
% 2021-10-31 you can use
idl = dataTable.date == '2021-10-31'
data = table2array(dataTable(idl,2:end))
4 comentarios
Más respuestas (1)
Stephen23
el 11 de Jul. de 2022
Editada: Stephen23
el 11 de Jul. de 2022
A much better approach stores the imported data in the structure returned by DIR:
P = 'absolute or relative path to where the files are saved';
S = dir(fullfile(P,'*.mat'));
for k = 1:numel(S)
F = fullfile(P,S(k).name);
T = load(F);
S(k).data = table2array(T.data);
end
All of the imported data will be available in the structure S, for example the 2nd file:
S(2).name
S(2).data
0 comentarios
Ver también
Categorías
Más información sobre Structures en Help Center y File Exchange.
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!