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**show

## 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 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:

- Python NumPy Sum + Examples
- Python NumPy Matrix Multiplication
- Python Tkinter Mainloop with Examples
- Python Tkinter Scrollbar – How to use
- Check if NumPy Array is Empty in Python + Examples

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

Entrepreneur, Founder, Author, Blogger, Trainer, and more. Check out my profile.