Last Updated : 24 Jan, 2025
numpy.arange() function creates an array of evenly spaced values within a given interval. It is similar to Python's built-in range() function but returns a NumPy array instead of a list.
Let's understand with a simple example:
Python
import numpy as np
#create an array
arr= np.arange(5 , 10)
print(arr)
Syntax of numpy.arange():
numpy.arange([start, ]stop, [step, ]dtype=None, *, like=None)
Parameters of numpy():
Return Type:
Generate a sequence of integers starting from 5 to 14.
Python
import numpy as np
# Creating a sequence of numbers from 0 to 9
sequence = np.arange(10)
print("Basic Sequence:", sequence)
Basic Sequence: [0 1 2 3 4 5 6 7 8 9]Floating-Point Step Size
Generate a sequence of floating-point numbers.
Python
import numpy as np
# Creating a sequence of floating-point numbers from 0 to 1
# with a step size of 0.2 using np.arange()
sequence = np.arange(0, 1, 0.2)
print("Floating-Point Sequence:", sequence)
Floating-Point Sequence: [0. 0.2 0.4 0.6 0.8]Combining with Conditional Filtering
Generate a sequence and filter specific values.
Python
import numpy as np
# Creating a sequence of numbers from 0 to 20
sequence = np.arange(0, 20, 3)
# Filtering the sequence to include only values greater than 10
filtered = sequence[sequence > 10]
print("Filtered Sequence:", filtered)
Filtered Sequence: [12 15 18]
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