Create 2d array from 2 single dimensional array in Python

Question

I have 2 single-dimensional NumPy arrays

a = np.array([0, 4])
b = np.array([3, 2])

I want to create a 2d array of numbers

c = np.array([[0,1,2], [4,5]])

I can also create this using a for loop

EDIT: Updating loop based on @jtwalters comments

c = np.zeros(b.shape[0], dtype=object)
for i in range(b.shape[0]):
    c[i] = np.arange(a[i], a[i]+b[i])

How can I achieve this via vectorization/broadcasting?

I agree with your first comment. But np.arange(6).reshape(2,3) won't work. 2 rows should be np.arange(a[i], a[i]+b[i]) please note that 3 is not in my resulting array. — deepAgrawal
– deepAgrawal, Commented Jul 12, 2021 at 7:26

jtwalters · Accepted Answer · 2021-07-12 19:30:13Z

1

To create an ndarray from ragged nested sequences you must put dtype=object.

For example:

c = np.empty(b.shape[0], dtype=object)
for i in range(b.shape[0]):
    c[i] = np.arange(a[i], a[i]+b[i])

np.array([np.arange(a[i], a[i]+b[i]) for i in range(b.shape[0])], dtype=object)

Vectorized:

def func(a, b):
  return np.arange(a, a + b)

vfunc = np.vectorize(func, otypes=["object"])
vfunc([0, 4], [3, 2])

answered Jul 12, 2021 at 7:54

jtwalters

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2 Comments

Is there a way to vectorize this?

@deepAgrawal Yes, I update the code with np.vectorize