Python NumPy Arange + Examples

In this Python tutorial, we will discuss Python NumPy arange and also cover the below points:

Python NumPy arange float
Python NumPy arange reverse
Python NumPy arange round
Python NumPy arange vs linspace
Python NumPy arange 2d
Python NumPy arange reshape
Python NumPy arange example
Python NumPy arange datetime

Table of Contents

Python numpy arange

If you are new to Python NumPy, check out Python Numpy.

In this section, we will learn about Python numpy arange.
The Numpy arange function generates a NumPy array with evenly spaced values based on the start and stops intervals specified upon declaration.
To use the arange function, we will create a new script with the NumPy library imported as np.
Next, we will declare a new variable number and set this equal to np. arange().
When we print the data type of the variable numbers to the console using the type function, we see its data type is a numpy array.
When we only pass in a single argument to the arange function, this value is the end value that is not included in the resulting array.
The default range for this function starts at 0 which is included and ends at the value specified as an argument, which is not included.

Syntax:

Here is the syntax of numpy.arange()

numpy.arange(
             [start],
             stop,
             [step],
             dtype=None
            )

Example:

import numpy as np

a = np.arange(2,10)
print(a)

Here is the Screenshot of following given code.

Read: Python NumPy to list

Python numpy arange float

In this section, we will learn about Python numpy arange float.
The Numpy arange function generates a NumPy array with evenly spaced values based on the start and stops intervals specified upon declaration.
In NumPy arange float, we can easily use the function np.arange to get the range of floating-point numbers.
It is a built-in range() function.
To use the arange function, we will create a new script with the NumPy library imported as np.

Syntax:

Here is the syntax of numpy arange float

numpy.arange(
             [start],
             stop,
             [step],
             dtype=float
            )

Start: The default value is 0. So this is the optional value if you didn’t define the start value it will take by default value zero.
Stop: It is also a number last of the interval that does not include this value so same to the built-in range functions the stop is not included but in some cases like this special cases it will include that when the step is not an integer value and floating-point round of effect the length of out.
Step: Spacing between values for any output is the distance between two adjacent values.
Dtype: stands for data type the type of the output numpy array if the data type is not given in for the dtype from the other input parameters.
Returns: It will return ndarray.

Example:

import numpy as np

a = np.arange(2,10,2,dtype = "float")
print(a)

Here is the Screenshot of following given code.

Read: Python NumPy Random + Examples

Python numpy arange reverse

In this section, we will learn about Python numpy arange reverse.
To reverse the number of elements in an array we can easily use the function numpy. flip().
The shape of the array is sustained, but the elements are reordered.
To use the arange function, we will create a new script with the numpy library imported as np.

Syntax:

Here is the syntax of numpy.flip() function

numpy.flip(
           a,
           axis=None
          )

Example

import numpy as np

a = np.arange(10)
a1= np.flip(a)
print(a1)

Here is the Screenshot of the following given code.

Python numpy arange round

In this section, we will learn about Python numpy arange round.
numpy.round() is a method that helps the user to rounds a numpy array to the given number of decimals.
To use the arange method, we will create a new script with the numpy library.
The rounded value is closest to the even value.

Syntax:

Here is the syntax of numpy.round()

numpy.round(
            arr,
            decimals,
            out=None
           )

Example

import numpy as np
a = np.array([0.345, 0.289, 0.221])
b=np.round(a, 1)
print(b)

Here is the Screenshot of the following given code

Read: Check if NumPy Array is Empty in Python + Examples

Python numpy arange vs linspace

In this section, we will learn about Python NumPy arange vs linspace.
numpy.linspace() and numpy.arange() methods are mostly similar because the np.linspace() method also declares an iterable sequence of evenly spaced values within a given interval.
It also gives values in the specified given interval and the elements are evenly spaced like numpy.arange() function.
The np.linspace() function will return an iterable sequence of evenly spaced values on that specific interval.

Syntax:

np.linspace(
            start,
            stop,
            endpoint=True,
            dtype=None,
            axis=0
            )

Example:

import numpy as np

a = np.arange(2,10,2)
b = np.linspace(0,10,5)
print(a)
print(b)

Here is the Screenshot of the following given code

Python NumPy Split

Python numpy arange 2d

In this section, we will learn about Python numpy arange 2d.
Two Dimensional array means the collection of homogenous data or number in lists of a list. It is also known as a numpy matrix. In a 2Dimension array, you have to use two square brackets that is why it is called lists of lists.
In numpy arange 2d, we can easily use a function that is np.reshape().
This np.reshape() function gives a new shape and size to a numpy array without changing its data.
To use the arange function, we will declare a new script with the numpy library.

Syntax:

Here is the syntax of numpy arange 2d

numpy.arange(
             [start],
             stop,
             [step],
             dtype=None
            )

Example:

import numpy as np

a = np.arange(2,6).reshape(2,2)
print(a)

Here is the Screenshot of the following given code.

Read: Python NumPy zeros + Examples

Python numpy arange reshape

In this section, we will learn and discuss Python NumPy arange reshape.
By reshaping we can add or delete dimensions or change the number of values in each dimension.
To use the numpy.arange() method and numpy.reshape() function we will create a newscript with the NumPy library imported as np.

Syntax:

Here is the syntax of numpy arange reshape

numpy.arange(
             [start],
             stop,
             [step],
             dtype=None
            )
            reshape()

Example:

import numpy as np

b = np.arange(2,8).reshape(3,2)
print(b)

Here is the Screenshot of following given code.

Python numpy arange example

In this section, we will learn about Python numpy arange.
Next, we will declare a new variable number and set this equal to np. arange().
When we print the data type of the variable numbers to the console using the type function, we see its data type is a numpy array.
When we only pass in a single argument to the arange function, this value is the end value that is not included in the resulting array.
The default range for this function starts at 0 which is included and ends at the value specified as an argument, which is not included.

Syntax:

Here is the syntax of numpy.arange()

numpy.arange(
             [start],
             stop,
             [step],
             dtype=None
            )

Example:

import numpy as np

a = np.arange(10)
print(a)

b = np.arange(2,20,2)
print(b)

c = np.arange(-5,-1)
print(c)

d = np.arange(0,10,2,dtype = "float")
print(d)

Here is the Screenshot of following code.

Python numpy arange datetime

In this section, we will learn about Python NumPy arange datetime.
The Numpy arange function generates a NumPy array with evenly spaced values based on the start and stops intervals specified upon declaration.
The datetime type works with many common NumPy, for example, arange can be used to generate a range of date functions.
To use the arange function, we will create a new script with the NumPy library imported as np.

Example:

import numpy as np

a = np.arange('2009-02', '2009-03', dtype='datetime64[D]')
print(a)

Here is the Screenshot of following given code

You may like the following Python tutorials:

In this Python tutorial, we will discuss Python numpy arange and also cover the below examples:

Python NumPy arange float
Python NumPy arange reverse
Python NumPy arange round
Python NumPy arange vs linspace
Python NumPy arange 2d
Python NumPy arange reshape
Python NumPy arange example
Python NumPy arange datetime

Bijay Kumar

I am Bijay Kumar, a Microsoft MVP in SharePoint. Apart from SharePoint, I started working on Python, Machine learning, and artificial intelligence for the last 5 years. During this time I got expertise in various Python libraries also like Tkinter, Pandas, NumPy, Turtle, Django, Matplotlib, Tensorflow, Scipy, Scikit-Learn, etc… for various clients in the United States, Canada, the United Kingdom, Australia, New Zealand, etc. Check out my profile.

enjoysharepoint.com/