How to convert continuous variable into discrete variables?

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I am looking for the help !!
I have 5000 rows of data points for three variables (independent variables-X1,x2,x3 and dependent variables Y). The x1 and x2 are discreate variables in fix steps. However, the X3 variables is countinous ranges from 0-0.6. I want to transfrom this varibles in steps of 0.05 upto 0.6 total in 12 steps and corroespoing value of Y variables should be mean of all values correspond between 0- 0.05 and so.
Well, i tried with find(x3<0.05) and got the index of all values which is less than 0.05. but struggling to compute mean(y) for the indices, mostly they are continous.
Plz help me.

Accepted Answer

Chetan Badgujar
Chetan Badgujar on 24 Aug 2020
HI Alan,
Thank you for you reply,
I tried but we are losing some information there..I attached the plot comparsion before and after converting the data, discreate data should follow the countinous data form.
load('DATA.mat');
X3(1) = []; % the first values for X3 and Y are NaNs, so they are removed here
Y(1) = [];
x3 = (0:0.05:2)';
Ydiscrete = zeros(length(x3),1);
for i = 2:length(x3)
ix = find(x3(i-1)<=X3<x3(i));
Ydiscrete(i) = mean(Y(ix));
end
plot(x3,Ydiscrete,'o')
hold on
scatter(X3,Y)
  2 Comments
Chetan Badgujar
Chetan Badgujar on 24 Aug 2020
HI Alan,
Well, I manuuly tried to compute this and explain very well in attached excel sheet Please go through it. The manual calculation sumarize it better way.
so WHat i did,
Step 1) find 0.05 in x and do average y( all values between 0-0.05)
Step 1) find 0.1 in x and do average y( all values between 0.05-0.1)
--- and so on until last value of x
It gives a great result you can check the excel sheet graph.
It would be great help even if You can convert all above steps into code.
Thank you once again.

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More Answers (3)

Alan Stevens
Alan Stevens on 23 Aug 2020
Does the following do what you want?
X3 = 0:0.05:0.6;
Ydiscrete = zeros(length(X3));
for i = 2:length(X3)
ix = find(X3(i-1)<=x3<X3(i));
Ydiscrete(i) = mean(Y(ix));
end
Untested, as I don't have the data!
  1 Comment
Chetan Badgujar
Chetan Badgujar on 24 Aug 2020
Hey, Alan Thanks for you reply.
I tired the given code, but it does not work. Well I have attached the data. Could you please test on that?
Thank you..

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Alan Stevens
Alan Stevens on 24 Aug 2020
How about this
load('DATA.mat');
X3(1) = []; % the first values for X3 and Y are NaNs, so they are removed here
Y(1) = [];
x3 = (0:0.05:0.6)';
Ydiscrete = zeros(length(x3),1);
for i = 2:length(x3)
ix = find(x3(i-1)<=X3<x3(i));
Ydiscrete(i) = mean(Y(ix));
end
plot(x3,Ydiscrete,'o')

Cris LaPierre
Cris LaPierre on 24 Aug 2020
Edited: Cris LaPierre on 26 Aug 2020
  3 Comments
Chetan Badgujar
Chetan Badgujar on 24 Aug 2020
@ Cris,
Thank you very much.. This is what I was looking for.. Its perfect with manual calculations.
Thank you once again.!!!

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