Generation of Probability Density Function and Confidence Intervals

Generation of Probability Density Function and Confidence Intervals

I'm trying to generate PDF's (or in this case "discrete PDF's").
I'am trying to use the numpy.random.normal(mu,sigma,size) but the function
does not take in consideration if the standard deviation was calculated
for 68%, 95% or 99%. The webpage says:
The function has its peak at the mean, and its "spread" increases with the
standard deviation (the function reaches 0.607 times its maximum at x +
sigma and x - sigma
What does this mean? The function assumes that the standard deviation is
at 60,7%?
Is there a function/package that generates a PDF taking in consideration
what confidence interval is associated with the standard deviation.
Note: The standard deviation i'm trying to input as argument are actually
expanded uncertainties which is why the confidence intervals are needed.