Replace missing time steps in dataset

I have a dataset with hourly measured data from 2013 to 2019. Some values are missing but not appearing in my dataset, and I want to include these values as NaN.

I have created a "true" time series:

%%

t1 = datenum(2013,10,1,0,0,0);

t2 = datenum(2019,10,1,0,0,0);

t = t1:(1/1440):t2;

And I also have the date number matrix,x, of my measurements, containing fewer elements. How can I fill in measured data in my new time series, and NaN where I dont have measurements?

I now have

t=52585x1 double

x=44719x1 double

Best regards,

Answer 1

[Toder]

If data is the vector of your measurements at times x, you can try

Y = NaN(size(t));
Y(ismember(t,x)) = data;