Creating a onedimensional NumPy array (original) (raw)
Creating a one-dimensional NumPy array
Last Updated : 27 Jan, 2025
**One-dimensional array contains elements only in one dimension. In other words, the shape of the NumPy 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.
Python `
import numpy as np
Create a one-dimensional array from a list
array_1d = np.array([1, 2, 3, 4, 5]) print(array_1d)
`
Let’s explore various methods to Create one- dimensional Numpy Array.
Table of Content
- Using Arrange()
- Using Linspace()
- Using Fromiter()
- Using Zeros()
- Using Ones() Function
- Using Random() Function
Using **Arrange()
**arrange()returns evenly spaced values within a given interval.
Python `
importing the module
import numpy as np
creating 1-d array
x = np.arange(3, 10, 2) print(x)
`
Using L**inspace()
L**inspace()creates evenly space numerical elements between two given limits.
Python `
import numpy as np
creating 1-d array
x = 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.
Python `
import numpy as np
creating the string
str = "geeksforgeeks"
creating 1-d array
x = 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
Python `
import numpy as np
arr5 = np.zeros(5) print(arr5)
`
**Output:
[0.0.0.0.0]
U**sing Ones() Function
**ones()returns the numbers of 1s as passed in the parameter of the method
Python `
import numpy as np
arr6 = np.ones(5) print(arr6)
`
**Using Random() Function
**Random() return the random module provides various methods to create arrays filled with random values.
Python `
import numpy as np
a=np.random.rand(2,3)
print(a)
`
Output
[[0.07752187 0.74982957 0.53760007] [0.73647835 0.62539542 0.27565598]]