This works:
a = [[1, 2, 3], [4, 5, 6]]
nd_a = np.array(a)
So this should work too:
nd_a = np.array([[x for x in y] for y in a])
Python Guides
pythonguides.com › python-numpy-2d-array
Create A 2D NumPy Array In Python (5 Simple Methods)
May 9, 2025 - Cells, rows, columns and slices of a 2D sales array. import numpy as np matrix = [[1, 2], [3, 4]] matrix.append([5, 6]) # add a row to a nested list for row in matrix: row.append(0) # add a column print(matrix) arr = np.array([[1, 2], [3, 4]]) ...
W3Schools
w3schools.com › python › numpy › numpy_creating_arrays.asp
NumPy Creating Arrays
An array that has 1-D arrays as its elements is called a 2-D array. These are often used to represent matrix or 2nd order tensors. NumPy has a whole sub module dedicated towards matrix operations called numpy.mat
03:09
How to create a Numpy 2D Array in Python | Complete Guide | Examples ...
03:13
Python NumPy | 2D Arrays - YouTube
07:09
Python Basics for Data Science - Numpy 2D Arrays - YouTube
03:58
Creating Two Dimensional Array in NumPy | NumPy in Python Tutorial ...
12:13
Multidimensional array Numpy (1D, 2D, 3D array )| how to create ...
Sentry
sentry.io › sentry answers › python › define a two-dimensional array in python
Python Define a Two-Dimensional Array or Matrix | Sentry
September 23, 2026 - The following code will create a 3-by-3 2D array with all values set to zero: import numpy matrix = numpy.zeros((3,3)) # array([[0., 0., 0.], # [0., 0., 0.], # [0., 0., 0.]])
Top answer 1 of 3
21
This works:
a = [[1, 2, 3], [4, 5, 6]]
nd_a = np.array(a)
So this should work too:
nd_a = np.array([[x for x in y] for y in a])
2 of 3
11
To create a new array, it seems numpy.zeros is the way to go
import numpy as np
a = np.zeros(shape=(x, y))
You can also set a datatype to allocate it sensibly
>>> np.zeros(shape=(5,2), dtype=np.uint8)
array([[0, 0],
[0, 0],
[0, 0],
[0, 0],
[0, 0]], dtype=uint8)
>>> np.zeros(shape=(5,2), dtype="datetime64[ns]")
array([['1970-01-01T00:00:00.000000000', '1970-01-01T00:00:00.000000000'],
['1970-01-01T00:00:00.000000000', '1970-01-01T00:00:00.000000000'],
['1970-01-01T00:00:00.000000000', '1970-01-01T00:00:00.000000000'],
['1970-01-01T00:00:00.000000000', '1970-01-01T00:00:00.000000000'],
['1970-01-01T00:00:00.000000000', '1970-01-01T00:00:00.000000000']],
dtype='datetime64[ns]')
See also
- How do I create an empty array/matrix in NumPy?
- np.full(size, 0) vs. np.zeros(size) vs. np.empty()
Programiz
programiz.com › python-programming › numpy › ndarray-creation
NumPy N-D Array Creation (With Examples)
May 22, 2023 - The np.zeros() function allows us to create N-D arrays filled with all zeros. For example, ... # create 2D array with 2 rows and 3 columns filled with zeros array1 = np.zeros((2, 3)) print("2-D Array: ") print(array1)
Drbeane
drbeane.github.io › python_dsci › pages › array_2d.html
2-Dimensional Arrays — Python for Data Science
Notice that the array that is printed above is not displayed in the form of a column. In fact, when slicing a single row or a column out of a 2D array, the result is returned as a simple 1D array. Every Numpy array comes equipped with a shape attribute that we can use to determine the shape of the array.
Medium
medium.com › @bouimouass.o › what-does-a-numpy-2d-array-look-like-in-python-38752ccde895
What does a numpy 2D array look like in python? | by Omar | Medium
July 23, 2023 - import numpy as np # Create a 2D array with 3 rows and 4 columns array = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]) # Print the array print(array)
NumPy
numpy.org › doc › stable › reference › arrays.ndarray.html
The N-dimensional array (ndarray) — NumPy v2.5 Manual
An ndarray is a (usually fixed-size) multidimensional container of items of the same type and size. The number of dimensions and items in an array is defined by its shape, which is a tuple of N non-negative integers that specify the sizes of each dimension.
w3resource
w3resource.com › python-exercises › numpy › python-numpy-exercise-37.php
Python NumPy: Create a 2-dimensional array of size 2 x 3 - w3resource
August 29, 2025 - ... # Importing the NumPy library with an alias 'np' import numpy as np # Creating a 2D NumPy array with two rows and three columns with data type np.int32 x = np.array([[2, 4, 6], [6, 8, 10]], np.int32) # Checking and displaying the type of ...
NumPy
numpy.org › doc › stable › user › basics.creation.html
Array creation — NumPy v2.5 Manual
For example: >>> import numpy as np >>> np.linspace(1., 4., 6) array([1. , 1.6, 2.2, 2.8, 3.4, 4. ]) The advantage of this creation function is that you guarantee the number of elements and the starting and end point. The previous arange(start, stop, step) will not include the value stop.
freeCodeCamp
freecodecamp.org › news › multi-dimensional-arrays-in-python
Multi-Dimensional Arrays in Python – Matrices Explained with Examples
December 11, 2025 - In this example, we create a 2-dimensional array using the np.array() function, and then use various NumPy functions to perform operations on the array.
Fabienmaussion
fabienmaussion.info › intro_to_programming › week_09 › 01-multidim-numpy.html
Multi-dimensional numpy arrays — Introduction to Programming
Copyright notice: parts of these examples are taken from the numpy tutorial for beginners. Multidimensional arrays are not different from 1 dimensional arrays. In fact, it is rather the 1 dimensional array which is a special case of the multidimensional one.
Indian AI Production
indianaiproduction.com › home › blog › python numpy array – create numpy ndarray (multidimensional array)
Python NumPy array - Create NumPy ndarray (multidimensional array)
June 12, 2019 - You can insert it while creating an array. import numpy as np # store student information in NumPy 2D array student_info = np.array([['id', 'name', 'percentage', 'pass or fail'], [101, 'Narendra', 80, 'pass'], [102, 'John', 75, 'pass'], [103, 'Abraham',33, 'fail'], [104, 'Oprah',52, 'pass'] ]) print(student_info)
GeeksforGeeks
geeksforgeeks.org › python › manipulating-multidimensional-arrays-in-python-numpy
Manipulating Multidimensional Arrays in Python NumPy - GeeksforGeeks
February 19, 2026 - Each nested structure represents a new dimension in the array. 1. 2D Array from List of Lists: NumPy's np.array() function can create a 2D array from a list of lists, where each sub-list represents a row in the array.
NumPy
numpy.org › devdocs › user › absolute_beginners.html
NumPy: the absolute basics for beginners — NumPy v2.6.dev0 Manual
This means that a 1D array will become a 2D array, a 2D array will become a 3D array, and so on. ... You can explicitly convert a 1D array to either a row vector or a column vector using np.newaxis. For example, you can convert a 1D array to a row vector by inserting an axis along the first ...
NumPy
numpy.org › doc › 2.2 › reference › arrays.ndarray.html
The N-dimensional array (ndarray) — NumPy v2.2 Manual
An ndarray is a (usually fixed-size) multidimensional container of items of the same type and size. The number of dimensions and items in an array is defined by its shape, which is a tuple of N non-negative integers that specify the sizes of each dimension.
Sdsu
gawron.sdsu.edu › python_for_ss › course_core › book_draft › data › numpy.html
6.2. More on two-dimensional arrays — python_for_ss 0.1.1 documentation
Boolean operations work more or less as expected on 2D arrays: import numpy as np y = np.arange(35).reshape(5,7) y>3
NumPy
numpy.org › devdocs › user › quickstart.html
NumPy quickstart — NumPy v2.6.dev0 Manual
The dots (...) represent as many colons as needed to produce a complete indexing tuple. For example, if x is an array with 5 axes, then ... >>> c = np.array([[[ 0, 1, 2], # a 3D array (two stacked 2D arrays) ... [ 10, 12, 13]], ... [[100, 101, 102], ...
MLJAR
mljar.com › answers › define-two-dimensional-array-python
Define two-dimensional array in Python
array[2][2] = 5 # valid array[7][2] = 3 # error · This way is much easier. You can use zeros function from numpy to create 2D array with all values set to zero: import numpy array = numpy.zeros((4,4)) REMEMBER Even though the second version is easier, the first one is better for this operation unless we need any matrix operations.
DataCamp
campus.datacamp.com › courses › intro-to-python-for-data-science › chapter-4-numpy
Your First 2D NumPy Array | Python
import numpy as np baseball = [[180, 78.4], [215, 102.7], [210, 98.5], [188, 75.2]] # Create a 2D numpy array from baseball: np_baseball # Print out the type of np_baseball # Print out the shape of np_baseball