# 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

## 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.

## 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
)``````
1. 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.
2. 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.
3. Step: Spacing between values for any output is the distance between two adjacent values.
4. 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.
5. 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.

## 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

## 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 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.

## 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

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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