Convert Z-score (Z-value, standard score) to p-value for normal distribution in Python
How does one convert a Z-score from the Z-distribution (standard normal distribution, Gaussian distribution) to a p-value? I have yet to find the magical function in Scipy's stats module to do this, but one must be there.
Answer
I like the survival function (upper tail probability) of the normal distribution a bit better, because the function name is more informative:
p_values = scipy.stats.norm.sf(abs(z_scores)) #one-sided
p_values = scipy.stats.norm.sf(abs(z_scores))*2 #twosided
normal distribution "norm" is one of around 90 distributions in scipy.stats
norm.sf also calls the corresponding function in scipy.special as in gotgenes example
small advantage of survival function, sf: numerical precision should better for quantiles close to 1 than using the cdf