Multiplying row in NumPy array by specific values based on another row

Question

I have the following list:

ls = [[1,2,3], [3,4] , [5] , [7,8], [23], [90, 81]]

This is my numpy array:

array([[    1,     0,     4,     3],
       [   10,   100,  1000, 10000]])

I need to multiply the values in the second row of my array by the length of the list in ls which is at the index of the corresponding number in the first row:

10 * len(ls[1]) & 100 * len(ls[0]) etc..

The objective output would be this array:

array([[    1,     0,     4,     3],
       [   20,   300,  1000, 20000]])

Any efficient way doing this?

Space Impact · Accepted Answer · 2018-10-31 06:17:18Z

3

Use list comprehesion to find lengths and multiply it with 2nd row of array as:

ls = [[1,2,3], [3,4] , [5] , [7,8]]
arr = np.array([[    1,     0,     2,     3],
                [   10,   100,  1000, 10000]])

arr[1,:] = arr[1,:]*([len(l) for l in ls])

arr
array([[    1,     0,     2,     3],
       [   30,   200,  1000, 20000]])

EDIT :

arr[1,:] = arr[1,:]*([len(ls[l]) for l in arr[0,:]])

arr
array([[    1,     0,     2,     3],
       [   20,   300,  1000, 20000]])

edited Oct 31, 2018 at 6:17

answered Oct 31, 2018 at 5:58

Space Impact

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1 Comment

Justin Lange Over a year ago

This answer it not correct. Compare your output with by objective output. Maybe I have formed my question not clearly. Instead of 30, is should be 20, since the corresponding value in the first row is 1. Thus, 10 * len(ls[1]) = 20 and not 30

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