Blind0ne Blind0ne - 2 months ago 11
Python Question

Calculate mean of array with specific value from another array

I have these numpy arrays:

array1 = np.array([-1, -1, 1, 1, 2, 1, 2, 2])
array2 = np.array([34.2, 11.2, 22.1, 78.2, 55.0, 66.87, 33.3, 11.56])


Now I want to return a 2d array in which there is the mean for each distinctive value from array1 so my output would look something like this:

array([[-1, 22.7],
[ 1, 55.7],
[ 2, 33.3]])


Is there an efficient way without concatenating those 1D arrays to one 2D array? Thanks!

Answer

Here's an approach using np.unique and np.bincount -

unq,ids,count = np.unique(array1,return_inverse=True,return_counts=True)
out = np.column_stack((unq,np.bincount(ids,array2)/count))

Sample run -

In [16]: array1 = np.array([-1, -1, 1, 1, 2, 1, 2, 2])
    ...: array2 = np.array([34.2, 11.2, 22.1, 78.2, 55.0, 66.87, 33.3, 11.56])
    ...: 

In [17]: unq,ids,count = np.unique(array1,return_inverse=True,return_counts=True)
    ...: out = np.column_stack((unq,np.bincount(ids,array2)/count))
    ...: 

In [18]: out
Out[18]: 
array([[ -1.        ,  22.7       ],
       [  1.        ,  55.72333333],
       [  2.        ,  33.28666667]])