hello everyone please can someone help me with stock price prediction. That is I wrote this code and from the I vector , I want a code that will remove indexes from the I vector more than 60 seconds. Thanks

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LSE_matrix =log(nstock_val); %log of the data
I=1:(size(LSE_matrix,1)-1); % selecting the indices of all prices but the last time when stock was opened
dLSE_col1 = LSE_matrix(I+1,1) - LSE_matrix(I,1);% log difference
Afua Amoako Dadey
Afua Amoako Dadey on 6 Jul 2020
Atttached is of picture the corresponding times. So say we consider 498 and 498. its more than 60 sec. how do i write a code to remove such an index. Thanks for the help.

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Accepted Answer

jonas on 6 Jul 2020
Edited: jonas on 6 Jul 2020
You can adapt this to your needs
A = readtable('LSE1.csv')
t = datetime(A{:,1},'inputformat','dd.MM.yyyy HH:mm:ss.SSS')
data = A{:,2:end};
id = [false;diff(t)>seconds(60)];
data(id,:) = [];
t(id) = [];
If the period between t(n) and t(n+1) is longer than 60s, then the data recorded at t(n+1) is deleted.
jonas on 9 Jul 2020
Edited: jonas on 9 Jul 2020
I don't understand exactly what the problem is, but I'm not a big fan of how you structure the data. I would put all my .csv files in a separate folder and read them as follows:
addpath('C:\files\') % change this to the correct path
files = dir('C:\files\*.csv'); % again..
for i = 1:numel(files)
opts = detectImportOptions(files(i).name);
opts.VariableTypes{1} = 'datetime';
opts = setvaropts(opts,'GmtTime','inputformat','dd.MM.yyyy HH:mm:ss.SSS');
A{i} = readtimetable(files(i).name,opts);
You will end up with 5 tables stored in cell array A. You can then append them to a single table or loop over each tables, no need to work with "Var1, Var2, Var3..."

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More Answers (1)

Afua Amoako Dadey
Afua Amoako Dadey on 6 Jul 2020
Please find attached


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