Can't decide if my data is normally distributed I have a problem comparing results from shapiro test and qqplot. Shapiro tells me my data doesn't have normal distribution characteristics (pvalue = 1.94...e-08 <= 0.05) however when I look on QQ plot the points are pretty close to the reference line.

How should I interpret that?
I'm using shapiro function from: https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.shapiro.html
 A: You should not worry too much about the return of the Shapiro-Wilk test, especially with higher sample sizes this can happen as already mentioned, the Q-Q plot looks fine.
Another option I would like to add is to simply visually inspect the data with a histogram, this can help some times more than a plain number given out by a normality Test.
You could use the histogram function from package numpy:
https://numpy.org/doc/stable/reference/generated/numpy.histogram.html#numpy.histogram
and get a result like this:

A: You seem to have quite a large sample size which is probably why the Shapiro-Wilk test returns a small p-value. In general statistical tests for normality are not a great idea in large part for this very reason.
There is some evidence, from the QQ plot, of slightly heavy tails. However, this is a fairly mild departure and in my opinion you are justified in considering these data to be approximately normally distributed.
I do wonder, however, why you are concerned about whether these data follow a normal distribution.
