List of lists into numpy array

Question

If your list of lists contains lists with varying number of elements then the answer of Ignacio Vazquez-Abrams will not work. Instead there are at least 3 options:

1) Make an array of arrays:

x=[[1,2],[1,2,3],[1]]
y=numpy.array([numpy.array(xi) for xi in x])
type(y)
>>><type 'numpy.ndarray'>
type(y[0])
>>><type 'numpy.ndarray'>

2) Make an array of lists:

x=[[1,2],[1,2,3],[1]]
y=numpy.array(x)
type(y)
>>><type 'numpy.ndarray'>
type(y[0])
>>><type 'list'>

3) First make the lists equal in length:

x=[[1,2],[1,2,3],[1]]
length = max(map(len, x))
y=numpy.array([xi+[None]*(length-len(xi)) for xi in x])
y
>>>array([[1, 2, None],
>>>       [1, 2, 3],
>>>       [1, None, None]], dtype=object)

>>> numpy.array([[1, 2], [3, 4]]) 
array([[1, 2], [3, 4]])

As this is the top search on Google for converting a list of lists into a Numpy array, I'll offer the following despite the question being 4 years old:

>>> x = [[1, 2], [1, 2, 3], [1]]
>>> y = numpy.hstack(x)
>>> print(y)
[1 2 1 2 3 1]

When I first thought of doing it this way, I was quite pleased with myself because it's soooo simple. However, after timing it with a larger list of lists, it is actually faster to do this:

>>> y = numpy.concatenate([numpy.array(i) for i in x])
>>> print(y)
[1 2 1 2 3 1]

Note that @Bastiaan's answer #1 doesn't make a single continuous list, hence I added the concatenate.

Anyway...I prefer the hstack approach for it's elegant use of Numpy.

It's as simple as:

>>> lists = [[1, 2], [3, 4]]
>>> np.array(lists)
array([[1, 2],
       [3, 4]])

Again, after searching for the problem of converting nested lists with N levels into an N-dimensional array I found nothing, so here's my way around it:

import numpy as np

new_array=np.array([[[coord for coord in xk] for xk in xj] for xj in xi], ndmin=3) #this case for N=3

The OP specified that "the rows are individual sublists and each row contains the elements in the sublist".

Assuming that the use of numpy is not prohibited (given that the flair numpy has been added in the OP), use vstack:

import numpy as np

list_of_lists= [[1, 2, 3], [4, 5, 6], [7 ,8, 9]]

array = np.vstack(list_of_lists)
# array([[1, 2, 3],
#        [4, 5, 6],
#        [7, 8, 9]])

or simpler (as mentioned in another answer),

array = np.array(list_of_lists)