Algorythm for Average of excel data
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Dear Sir please suggest .. How can I get average of my attached data in excel at an interval of every 5 datas. like at time interval 0-0.5 sec then 0.6-1 sec, 1-1.5 sec and so on....
1 commentaire
Jon
le 21 Fév 2024
Modifié(e) : Jon
le 23 Fév 2024
You have a lot of what look like helpful answers to your question. Unless, there is something that has not been addressed in these answers, it would be good for you to now select one of them as the answer. This will allow the question to be marked as answered so that others will know that an answer is available.
Réponse acceptée
Dyuman Joshi
le 15 Fév 2024
Modifié(e) : Dyuman Joshi
le 15 Fév 2024
data = readtable('S1IA.csv')
%define bins to distribute bins in
idx = 0:0.5:0.5*ceil(max(data.Time)/0.5);
%Get the mean of the rest of the columns for the specified bins
out = groupsummary(data, 1, idx, @mean, 'IncludedEdge', 'right')
3 commentaires
Plus de réponses (4)
Jon
le 15 Fév 2024
Modifié(e) : Jon
le 15 Fév 2024
If you have the Statistics and Machine learning toolbox you could do it like this
% Parameters
grpIncr = 0.5 % time increment for group averages
% Read the data into a matrix
dat = readmatrix('S1IA.csv')
% Provide grouping variable that makes elements within a specified sampling
% interval have the same group value
grp = floor(dat(:,1)/0.5);
[dat grp]
% Calculate mean of each group
stats = grpstats(dat(:,2:3),grp)
3 commentaires
Voss
le 15 Fév 2024
Maybe something like this:
filename = 'S1IA.csv';
T = readtable(filename);
T.Time = seconds(T.Time);
T = table2timetable(T,'RowTimes','Time');
new_t = T.Time(1):seconds(0.5):T.Time(end);
T = retime(T,new_t,'mean')
0 commentaires
Mathieu NOE
le 15 Fév 2024
hello again
well, this is quite the same as my answer to your other post
adapted to your new data file , this becomes :
data = readmatrix('S1IA.csv'); % Time,A,B
t = data(:,1);
dt = mean(diff(t));
%% home made solution (you choose the amount of overlap)
buffer_size = round(0.5/dt); % how many samples for 0.5 seconds buffer ?
overlap = 0; % overlap expressed in samples
%%%% main loop %%%%
[new_time,data_out] = my_movmean(t,data(:,2:3),buffer_size,overlap);
figure(2),
plot(t,data(:,2),new_time,data_out(:,1),'*-r');
title('A');
legend('raw data','0.5s mean');
xlabel('Time(s)');
figure(3),
plot(t,data(:,3),new_time,data_out(:,2),'*-r');
title('B');
legend('raw data','0.5s mean');
xlabel('Time(s)');
%%%%%%%%%% my functions %%%%%%%%%%%%%%
function [new_time,data_out] = my_movmean(t,data_in,buffer_size,overlap)
% NB : buffer size and overlap are integer numbers (samples)
% data (in , out) are 1D arrays (vectors)
shift = buffer_size-overlap; % nb of samples between 2 contiguous buffers
[samples,~] = size(data_in);
nb_of_loops = fix((samples-buffer_size)/shift +1);
for k=1:nb_of_loops
start_index = 1+(k-1)*shift;
stop_index = min(start_index+ buffer_size-1,samples);
x_index(k) = round((start_index+stop_index)/2);
data_out(k,:) = mean(data_in(start_index:stop_index,:),1,'omitnan'); %
end
new_time = t(x_index); % time values are computed at the center of the buffer
end
Alexander
le 15 Fév 2024
A very easy approach (as allways):
%Algorythm for Average of excel data
%https://de.mathworks.com/matlabcentral/answers/2082483-algorythm-for-average-of-excel-data
clear; close all;
data = dlmread('S1IA.csv',',',1,0);
t = data(:,1);A = data(:,2);B = data(:,3);
dy = floor(length(A)/5)
t = t(1:dy*5); % maximum 4 samples lost!
tr = reshape(t,5,dy);
trMean = mean(tr);
A = A(1:dy*5); % maximum 4 samples lost!
Ar = reshape(A,5,dy);
ArMean = mean(Ar);
B = B(1:dy*5); % maximum 4 samples lost!
Br = reshape(B,5,dy);
BrMean = mean(Br);
subplot(211)
plot(trMean ,ArMean); grid minor; title('A')
subplot(212)
plot(trMean, BrMean); grid minor; title('B')
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