In this tutorial, we will introduce some methods to create array in NumPy.

1. The most common way is to create an array using a python list.

import numpy as np 
 
array = np.array([[1, 2], [3, 4]])

2. We also can use some numpy methods to create numpy array.

There are some numpy methods that allow us to create numpy array. Here is a list:

Function	Description
empty()	Return a new array of given shape and type, without initializing entries
empty_like()	Return a new array with the same shape and type as a given array
eye()	Return a 2-D array with ones on the diagonal and zeros elsewhere.
identity()	Return the identity array
ones()	Return a new array of given shape and type, filled with ones
ones_like()	Return an array of ones with the same shape and type as a given array
zeros()	Return a new array of given shape and type, filled with zeros
zeros_like()	Return an array of zeros with the same shape and type as a given array
full_like()	Return a full array with the same shape and type as a given array.
array()	Create an array
asarray()	Convert the input to an array
asanyarray()	Convert the input to an ndarray, but pass ndarray subclasses through
ascontiguousarray()	Return a contiguous array in memory (C order)
asmatrix()	Interpret the input as a matrix
copy()	Return an array copy of the given object
frombuffer()	Interpret a buffer as a 1-dimensional array
fromfile()	Construct an array from data in a text or binary file
fromfunction()	Construct an array by executing a function over each coordinate
fromiter()	Create a new 1-dimensional array from an iterable object
fromstring()	A new 1-D array initialized from text data in a string
loadtxt()	Load data from a text file
arange()	Return evenly spaced values within a given interval
linspace()	Return evenly spaced numbers over a specified interval
logspace()	Return numbers spaced evenly on a log scale
geomspace()	Return numbers spaced evenly on a log scale (a geometric progression)
meshgrid()	Return coordinate matrices from coordinate vectors
mgrid()	nd_grid instance which returns a dense multi-dimensional “meshgrid
ogrid()	nd_grid instance which returns an open multi-dimensional “meshgrid
diag()	Extract a diagonal or construct a diagonal array
diagflat()	Create a two-dimensional array with the flattened input as a diagonal
tri()	An array with ones at and below the given diagonal and zeros elsewhere
tril()	Lower triangle of an array
triu()	Upper triangle of an array
vander()	Generate a Vandermonde matrix
mat()	Interpret the input as a matrix
bmat()	Build a matrix object from a string, nested sequence, or array

For example, we can create a zero array.

a = np.zeros([2, 2], dtype = int)
print(a)

NumPy array a will be:

[[0 0]

 [0 0]]