title: What does 'index 0 is out of bounds for axis 0 with size 0' mean?
body: <p>I am new to both python and numpy.
  I ran a code that I wrote and I am getting this message:
  'index 0 is out of bounds for axis 0 with size 0'
  Without the context, I just want to figure out what this means.. It might be silly to ask this but what do they mean by axis 0 and size 0? index 0 means the first value in the array.. but I can't figure out what axis 0 and size 0 mean. </p>
  
  <p>The 'data' is a text file with lots of numbers in two columns. </p>
  
  <pre><code>x = np.linspace(1735.0,1775.0,100)
  column1 = (data[0,0:-1]+data[0,1:])/2.0
  column2 = data[1,1:]
  x_column1 = np.zeros(x.size+2)
  x_column1[1:-1] = x
  x_column1[0] = x[0]+x[0]-x[1]
  x_column1[-1] = x[-1]+x[-1]-x[-2]
  experiment = np.zeros_like(x)
  for i in range(np.size(x_edges)-2):
      indexes = np.flatnonzero(np.logical_and((column1&gt;=x_column1[i]),(column1&lt;x_column1[i+1])))
      temp_column2 = column2[indexes]
      temp_column2[0] -= column2[indexes[0]]*(x_column1[i]-column1[indexes[0]-1])/(column1[indexes[0]]-column1[indexes[0]-1])
      temp_column2[-1] -= column2[indexes[-1]]*(column1[indexes[-1]+1]-x_column1[i+1])/(column1[indexes[-1]+1]-column1[indexes[-1]])
      experiment[i] = np.sum(temp_column2)   
  return experiment
  </code></pre>