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I'm trying to fit some data and stuff, I know there is a simple command to do this with python/numpy/matplotlib, but I can't find it. I think it is something like 

popt,popc = numpy.curvefit(f,x)

where popt is the paramters of f, popc is the fit quality and f is a predefined function of f. Does any of you know it?

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    If this is a one-off, it's easier to just plug the values into the function finder at zunzun.com and let it find the best matching curve. Their Python code is available, too. Commented Dec 2, 2011 at 14:57

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Take a look at scipy.optimize.curve_fit:

scipy.optimize.curve_fit(f, xdata, ydata, p0=None, sigma=None, **kw)

Use non-linear least squares to fit a function, f, to data.

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One question: is there an easy way to get R-squared value out of curve_fit, or get SSE so that I can calculate R-squared? I can do some work and get it done in scipy.optimize.leastsq, but the code will be much more verbose.
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Found it. Curve_fit from optimize in scipy

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Isn't this answer a duplicate of the accepted answer?

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