title: Numba failure with np.mean
body: <p>For some reason, numba fails when I add in a axis argument to np.mean. For instance, this gives an error -  </p>
  
  <pre><code>import numpy as np
  from numba import jit
  @jit(nopython=True)
  def num_prac(a):
      return np.mean(a,-1)
  
  b=np.array([[1,2,3,4,5],[1,2,3,4,5]])
  print(num_prac(b))
  
  TypingError: Invalid use of Function(&lt;function mean at 0x000002949B28E1E0&gt;) with argument(s) of type(s): (array(int32, 2d, C), Literal[int](1))
   * parameterized
  In definition 0:
      AssertionError: 
      raised from C:\ProgramData\Anaconda3\lib\site-packages\numba\typing\arraydecl.py:649
  In definition 1:
      AssertionError: 
      raised from C:\ProgramData\Anaconda3\lib\site-packages\numba\typing\arraydecl.py:649
  This error is usually caused by passing an argument of a type that is unsupported by the named function.
  [1] During: resolving callee type: Function(&lt;function mean at 0x000002949B28E1E0&gt;)
  [2] During: typing of call at C:/Users/U374235/test.py (11)
  </code></pre>
  
  <p>However, this works perfectly - </p>
  
  <pre><code>import numpy as np
  from numba import jit
  @jit(nopython=True)
  def num_prac(a):
      return np.mean(a)
  
  b=np.array([[1,2,3,4,5],[1,2,3,4,5]])
  print(num_prac(b))
  </code></pre>