Evenly round to the given number of decimals.
Parameters:  a : array_like
decimals : int, optional
out : ndarray, optional


Returns:  rounded_array : ndarray

Notes
For values exactly halfway between rounded decimal values, Numpy rounds to the nearest even value. Thus 1.5 and 2.5 round to 2.0, 0.5 and 0.5 round to 0.0, etc. Results may also be surprising due to the inexact representation of decimal fractions in the IEEE floating point standard [R16] and errors introduced when scaling by powers of ten.
References
[R16]  (1, 2) “Lecture Notes on the Status of IEEE 754”, William Kahan, http://www.cs.berkeley.edu/~wkahan/ieee754status/IEEE754.PDF 
[R17]  “How Futile are Mindless Assessments of Roundoff in FloatingPoint Computation?”, William Kahan, http://www.cs.berkeley.edu/~wkahan/Mindless.pdf 
Examples
>>> np.around([0.37, 1.64])
array([ 0., 2.])
>>> np.around([0.37, 1.64], decimals=1)
array([ 0.4, 1.6])
>>> np.around([.5, 1.5, 2.5, 3.5, 4.5]) # rounds to nearest even value
array([ 0., 2., 2., 4., 4.])
>>> np.around([1,2,3,11], decimals=1) # ndarray of ints is returned
array([ 1, 2, 3, 11])
>>> np.around([1,2,3,11], decimals=1)
array([ 0, 0, 0, 10])