Get mean and stdev from all values
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Hi,
I have a list like below. in the first column I have values from 0 to 91 (there can miss values).
0 3
0 4.50000000000000
0 1.37500000000000
0 5
0 3
0 0.838961038961039
0 2.80000000000000
1 1.50000000000000
1 0.555555555555556
1 1.71428571428571
1 3.38666666666667
1 4
1 3.38666666666667
2 1.73684210526316
2 1
2 1.30769230769231
2 2.73333333333333
2 1
2 2
I want to calculate the mean and standard deviation for all of these values if they exist.
How can I realise this? Now I have the folowing:
clear all; clc; close all;
standaard = readmatrix('/Users/diontheunissen/Documents/Apployee/Smart_driver/avgFuel.xlsx');
indices = find(standaard(:,1)==0);
standaard(indices,:) = [];
indices = find(standaard(:,2)>8);
standaard(indices,:) = [];
standaard(:,1) = round(standaard(:,1));
standaard = sortrows(standaard,1);
c = {};
for i = 0:5:85
if i == 0
lower = find(standaard(:,1) == i);
n = i+5;
upper = find(standaard(:,1) == n);
elseif i>1
lower = find(standaard(:,1) == i+1);
n = i+5;
upper = find(standaard(:,1) == n);
end
tab = standaard(lower(1):upper(end),:);
c{i+1} = tab;
end
referent2 = []
for j = 1:5:86
data = cell2mat(c(j));
referent(1,1) = data(1,1);
referent(1,2) = mean(data(:,2));
referent(1,3) = std(data(:,2));
referent2 = [referent2;referent]
end
snelheid = linspace(min(referent2(:,1)),max(referent2(:,1)));
a1 = interp1(referent2(:,1), referent2(:,2:end), snelheid, 'makima');
verbruik = a1(:,1);
upper = a1(:,1)+a1(:,2);
lower = a1(:,1)-a1(:,2);
figure
hold on
plot(snelheid, verbruik, '-b');
plot(snelheid, upper,'-r');
plot(snelheid, lower,'-g');
How can i change this script that i get the mean and stdev from all existing values?
thanks
2 Comments
DGM
on 3 Jun 2021
Can you clarify the structure of the file and what you're trying to do? I'm assuming you're trying to find the blockwise mean and std for column 2, the blocks being described by column 1. Are all blocks the same size? Are the values in column 1 sorted?
Accepted Answer
DGM
on 3 Jun 2021
Edited: DGM
on 3 Jun 2021
If column 1 is sorted:
% build test array
idx = repelem(1:10,randi(6,10,1));
idx = idx(1:20);
D = [idx.' rand(20,1)]; % the test array
% find length of blocks
blocklengths = diff([0 find(diff(idx)) numel(idx)]);
% split and process
C = mat2cell(D(:,2),blocklengths,1);
bkmean = cellfun(@mean,C)
bkstd = cellfun(@std,C)
0 Comments
More Answers (1)
Stephan
on 3 Jun 2021
Edited: Stephan
on 3 Jun 2021
Use a table and then use findgroups combined with splitappy. This will allow you to solve the problem with a few lines of code. This will also work if the columns are not sorted.
1 Comment
Steven Lord
on 3 Jun 2021
findgroups can operate on numeric data as well as tabular data.
But rather than call those two functions sequentially, I'd probably just use groupsummary.
X = [0 3;
0 4.50000000000000;
0 1.37500000000000;
0 5;
0 3;
0 0.838961038961039;
0 2.80000000000000;
1 1.50000000000000;
1 0.555555555555556;
1 1.71428571428571;
1 3.38666666666667;
1 4;
1 3.38666666666667;
2 1.73684210526316;
2 1;
2 1.30769230769231;
2 2.73333333333333;
2 1;
2 2];
[M, BG] = groupsummary(X(:, 2), X(:, 1), @mean)
check = mean(X(X(:, 1)== 1, 2)) % This is the same as M(BG == 1)
S = groupsummary(X(:, 2), X(:, 1), @std)
MS = groupsummary(X(:, 2), X(:, 1), {@mean, @std}) % Compute M and S simultaneously
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