Multiply different size nested array with scalar-CodePudding

In my python code, I have an array that has different size inside like this

arr = [
    [1],
    [2,3], 
    [4],
    [5,6,7],
    [8],
    [9,10,11]
]

I want to multiply them by 10 so it will be like this

arr = [
        [10],
        [20,30], 
        [40],
        [50,60,70],
        [80],
        [90,100,110]
    ]

I have tried arr = np.multiply(arr,10) and arr = np.array(arr)*10

it seems that both are not working for different size of nested array because when I tried using same size nested array, they actually works just fine

CodePudding user response：

It is best to just use a nested loop :

arr = [
    [1],
    [2,3], 
    [4],
    [5,6,7],
    [8],
    [9,10,11]
]

def matrix_multiply_all(matrix,nb):
    return list(map(lambda arr : list(map(lambda el : el*nb,arr)),matrix))
print(matrix_multiply_all(arr,10))

CodePudding user response：

You can do with list comprehension as sahasrara62 mentioned if it is a list:

[[i*10 for i in x] for x in arr]

CodePudding user response：

You need not to use Numpy for this,

Here is the code:

for i in range(len(arr)):
    for j in range(len(arr[I])):
        arr[i][j] = arr[i][j]*10
print(arr)

Output:

[[10], [20, 30], [40], [50, 60, 70], [80], [90, 100, 110]]

Even though this give answer it is not pythonic. More Pythonic code:

arr = [[j * 10 for j in i] for i in arr]
print(arr)

Output:

[[10], [20, 30], [40], [50, 60, 70], [80], [90, 100, 110]]