title: Python: Numpy percentile confusing results
body: <p>When using the Python Numpy to calculate quantile/percentile, the results are a little bit weird as below. I am quite confused about this, could anyone explain why?</p>
  
  <pre class="lang-py prettyprint-override"><code>import numpy as np
  
  x = range(1,1031)
  x = np.array(x)
  
  np.percentile(x,1,interpolation='lower')
  # 11
  np.percentile(x,1,interpolation='higher')
  # 12
  
  np.percentile(x,0.972,interpolation='lower')
  # 11
  np.percentile(x,0.972,interpolation='higher')
  # 12
  
  np.percentile(x,0.971,interpolation='lower')
  # 10
  np.percentile(x,0.971,interpolation='higher')
  # 11
  </code></pre>
  
  <p>I expect the lower and higher 1% quantiles of the numbers from 1 to 1030 to be 10 and 11, but the actual results are 11 and 12.</p>