One-dimensional arraycontains elements only in one dimension. In other words, the shape of theNumPy array should contain only one value in the tuple. We can create a 1-D array in NumPy using the array() function, which converts a Python list or iterable object.

importnumpyasnp# Create a one-dimensional array from a listarray_1d=np.array([1,2,3,4,5])print(array_1d)

[1 2 3 4 5]

Let's explore various methods to Create one- dimensional Numpy Array.

UsingArrange()

arrange()returns evenly spaced values within a given interval.

# importing the moduleimportnumpyasnp# creating 1-d arrayx=np.arange(3,10,2)print(x)

[3 5 7 9]

Using Linspace()

Linspace()creates evenly space numerical elements between two given limits.

importnumpyasnp# creating 1-d arrayx=np.linspace(3,10,3)print(x)

Output:

[ 3.   6.5 10. ]

Using Fromiter()

Fromiter()is useful for creating non-numeric sequence type array however it can create any type of array. Here we will convert a string into a NumPy array of characters.

importnumpyasnp# creating the stringstr="geeksforgeeks"# creating 1-d arrayx=np.fromiter(str,dtype='U2')print(x)

Output:

['g' 'e' 'e' 'k' 's' 'f' 'o' 'r' 'g' 'e' 'e' 'k' 's']

Using Zeros()

Zeros()returns the numbers of 0s as passed in the parameter of the method 

importnumpyasnparr5=np.zeros(5)print(arr5)

Output:

[0.0.0.0.0]

Using Ones() Function

ones()returns the numbers of 1s as passed in the parameter of the method 

importnumpyasnparr6=np.ones(5)print(arr6)

[1. 1. 1. 1. 1.]

Using Random() Function

Random()return the random module provides various methods to create arrays filled with random values.

importnumpyasnpa=np.random.rand(2,3)print(a)

[[0.07752187 0.74982957 0.53760007] [0.73647835 0.62539542 0.27565598]]

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