You may think it is easy, if only you can find someone who has the magic touch.
Sorry, but not so easy.
If the curve is presumed to be a straight line, this is an errors in variables problem, often called total least squares. That part is solvable without a great deal of difficulty. The trick is to use PCA. HOWEVER, this data does not fall on anything like a line.
Just looking at your data, it is not very clean.
So we see points at very discrete levels, scattered throughout space. I have no idea what line it is that you think represents that data. It also looks nothing at all like the picture you posted.
Even if we find that you posted the wrong data, there is still the problem of choosing a model. Until you choose some nonlinear model, there is no chance at all of finding "THE" function that represents it.
And then worst, nonlinear total least squares can be a difficult problem to solve.
I wish you luck, but there ain't no magic formula. And until you decide what the correct data is, and what model you expect to apply to approximate that data, you cannot find "THE" function that fits the data.