# Fetch Elements of a certain range from NumPy array in Python

In this tutorial, we will learn how to fetch elements of a certain range from NumPy array in Python with some basic and easy examples. In many situations, you may have to fetch elements over a certain range and NumPy helps us do that very easily.
It provides us 3 methods to fetch elements  in Python:

• The array( ) method
• The arange( ) method
• The linspace( ) method

## The array( ) method

array( ) method is included in NumPy library which enables us to convert a list into a NumPy array.
The array( ) method takes a list as an object in its argument and converts it to an array.
A simple example to convert a list to an array is shown below.

```#importing NumPy as np
import numpy as np

#declaring a list
ls = [1,2,3,4]

#converting the list into array
arr = np.array(ls)```
```Output:
array([1, 2, 3, 4])

```

We can also specify an additional argument such as datatype(referred as dtype) in the array( ) method. The default value of dtype is None. As a result, the output array will be the same as the input list.
Some examples to show the use of dtype argument are as shown.

```#importing NumPy as np
import numpy as np

#create a list
ls = [1,2,3,4,5,6]

#use of array()
arr = np.array(ls,dtype=float)```
```Output:
array([1., 2., 3., 4., 5., 6.])

```
```#importing NumPy as np
import numpy as np

#create a list(floating points)
ls = [1.04,3.14,3.14,5.56,8.07]

#use of array()
arr = np.array(ls,dtype=int)```
```Output:
array([1,3,3,5,8])```

We can also pass a list without defining it separately as an object argument.

```#importing NumPy as np
import numpy as np

#using array()
arr = np.array([1,2,3,4,5,6,7,8])```
```Output:
array([1,2,3,4,5,6,7,8])

```

## The arange() method

This method is also included in the NumPy library and is one of the most important method available. It takes in 4 parameters as its argument.

```Syntax:
np.array(start,stop,step,dtype)```

The start parameter is always inclusive and the stop parameter is always exclusive. Defining the datatype is optional and left to the user. Deafult step value 1.
example:

```#importing NumPy as np
import numpy as np

#use of arange()
arr = np.arange(0,10)```
```Output:
array([0,1,2,3,4,5,6,7,8,9])```

## The linspace( ) method

linspace( ) is another important method of NumPy used to fetch elements in Python. It is used to generate samples between the start value and the stop value with spacing between them by a number “num”. The default value of num is 50 and it must be non-negative. We can also pass the dtype as an argument which is by default set as None. The dtype should not be set as an integer as loss of data occurs.

```Syntax:
np.linspace(start,stop,num,dtype)```

Unlike arange() method, the stop value and the start values are inclusive. Some examples to show the use of linspace( ) are shown.

```#importing NumPy as np
import numpy as np

#use of linspace()
arr = np.linspace(0,10,10)```
```Output:
array([ 0.        ,  1.11111111,  2.22222222,  3.33333333,  4.44444444,
5.55555556,  6.66666667,  7.77777778,  8.88888889, 10.        ])```
```#importing NumPy as np
import numpy as np

#use of linspace()
#default value of num=50
arr = np.linspace(0,10)```
```Output:
array([ 0.        ,  0.20408163,  0.40816327,  0.6122449 ,  0.81632653,
1.02040816,  1.2244898 ,  1.42857143,  1.63265306,  1.83673469,
2.04081633,  2.24489796,  2.44897959,  2.65306122,  2.85714286,
3.06122449,  3.26530612,  3.46938776,  3.67346939,  3.87755102,
4.08163265,  4.28571429,  4.48979592,  4.69387755,  4.89795918,
5.10204082,  5.30612245,  5.51020408,  5.71428571,  5.91836735,
6.12244898,  6.32653061,  6.53061224,  6.73469388,  6.93877551,
7.14285714,  7.34693878,  7.55102041,  7.75510204,  7.95918367,
8.16326531,  8.36734694,  8.57142857,  8.7755102 ,  8.97959184,
9.18367347,  9.3877551 ,  9.59183673,  9.79591837, 10.        ])

```