title: Calculate P75/P90 value with given P50 and STD in Python
body: <p>I just started with my first steps in Python and I´d like to calculate from a yield estimation from a Wind Park (P50) and a given overall measurement uncertainty (std) the P75 and P90 value, with an underlying normal distribution. </p>
  
  <p>I tried for example:</p>
  
  <pre><code>P50 = 35556325 #kWh p.a.
  std = 0.13
  
  s = np.random.normal(P50, std, 0)
  </code></pre>
  
  <p>but I don´t know how to call then a certain P-value in the distribution. </p>
  
  <p>Is there an easy way to get fast the P75-value out of this? Or a different function?</p>
  
  <p>Certainly this is not a big thing, but I´m somehow stuck.</p>
  
  <p>Thanks a lot!</p>