python - List of lists into numpy array

Question

How do I convert a simple list of lists into a numpy array? The rows are individual sublists and each row contains the elements in the sublist.

Answer 1

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)

Answer 2

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

Answer 3

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.

Answer 4

It's as simple as:

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

Answer 5

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

Answer 6

I had a list of lists of equal length. Even then Ignacio Vazquez-Abrams's answer didn't work out for me. I got a 1-D numpy array whose elements are lists. If you faced the same problem, you can use the below method

Use numpy.vstack

import numpy as np

np_array = np.empty((0,4), dtype='float')
for i in range(10)
     row_data = ...   # get row_data as list
     np_array = np.vstack((np_array, np.array(row_data)))

Answer 7

Just use pandas

list(pd.DataFrame(listofstuff).melt().values)

this only works for a list of lists

if you have a list of list of lists you might want to try something along the lines of

lists(pd.DataFrame(listofstuff).melt().apply(pd.Series).melt().values)