PYTHON

python numpy array to list

# Basic syntax:
numpy_array.tolist()

# Example usage:
your_array = np.array([[1, 2, 3], [4, 5, 6]])
your_array
--> array([[1, 2, 3],
           [4, 5, 6]])

your_array.tolist()
--> [[1, 2, 3], [4, 5, 6]]

np.array to list

>>> a = np.array([1, 2])
>>> list(a)
[1, 2]
>>> a.tolist()
[1, 2]

from numpy to list python

import numpy as np

# 1d array to list
arr = np.array([1, 2, 3])
print(f'NumPy Array:
{arr}')
#NumPy Array: [1 2 3]

list1 = arr.tolist()
print(f'List: {list1}')
#List: [1, 2, 3]

convert list to numpy array

import numpy as np
npa = np.asarray(Lists, dtype=np.float32)

np array to list

# make np array 
np_arr = np.array(['a','b','c'])
# np array to list
py_list = np_arr.tolist()
print(py_list)
# output: ['a','b','c']

python numpy matrix to list

import numpy as np
x = np.matrix([[1,2,3],
               [7,1,3],
               [9,4,3]])
y = x.tolist()

y --> [[1, 2, 3], [7, 1, 3], [9, 4, 3]]

numpy array from list

>>> a = [1, 2]
>>> np.asarray(a)
array([1, 2])

convert list of lists to numpy array matrix python

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'>

list of list to numpy array

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

list of array to array numpy

np.concatenate( list_of_array, axis=0 )