how to remove outliers in large data sets?

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I am unable to open example code of outliers (openExample('matlab/RemoveOutliersInVectorExample') ) and openExample('matlab/DetermineOutliersWithStandardDeviationExample') also.
I had large datasets of power load for three years at 30min interval, I want to remove the outliers poitns which is affecting my forecasting error.
any help to remove the outliers in such datasets would be appreciated.
Thanks
Reference image is attached which shows the outliers datasets in upper side of image, reference to these points the error is also high (as lower side of image).
Thanks again
  2 Comments
MUKESH KUMAR
MUKESH KUMAR on 8 Jan 2022
Not in GB but its five years data having outliers data in patters, i am attaching data file here

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Accepted Answer

Image Analyst
Image Analyst on 8 Jan 2022
Try this:
data = readmatrix('Copy of data.xlsx');
x = data(:, 1);
y = data(:, 2);
% Plot just the first cycle.
last = round(70000/3)
x = x(1:last);
y = y(1:last);
subplot(2, 1, 1);
plot(x, y, 'b-')
grid on;
title('Showing One Cycle Only')
% Smooth the data.
windowWidth = 2001; % Some large odd number.
smoothY = movmean(y, windowWidth);
hold on;
plot(x, smoothY, 'r-', 'LineWidth', 3)
% Compute difference between actual and smoothed.
diffy = y - smoothY;
subplot(2, 1, 2);
plot(x, diffy, 'b-');
grid on;
% Detect outliers as having a MAD of more than 900
outlierIndexes = abs(diffy) > 900;
% Plot outliers as red dots over the original data.
subplot(2, 1, 1);
hold on
plot(x(outlierIndexes), y(outlierIndexes), 'r.', 'MarkerSize', 7);
% Now remove outliers from x and y
x(outlierIndexes) = [];
y(outlierIndexes) = [];
  2 Comments
Image Analyst
Image Analyst on 17 Jan 2022
You must have a version so old that rmoutliers was not in it yet. However you can do it manually. Just smooth the curve and subtract it from your data and threshold like I did. I didn't use rmoutliers.

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