# How to select elements from Numpy array in Python?

In this article, we will show you how to select elements from a NumPy array in python.

## Numpy Array in Python

A NumPy array is a central data structure of the NumPy library, as the name implies. The name of the library is an abbreviation for "Numeric Python" or "Numerical Python.

NumPy, in other words, is a Python library that serves as the foundation for scientific computing in Python. One of these tools is a high-performance multidimensional array object, which is a powerful data structure for efficient array and matrix computation.

We can select a single element or a subarray from a Numpy array at a time. Here now we see the following methods of selecting elements from the Numpy array.

• Selecting a single NumPy array element
• Selecting a sub-array from a NumPy array using slicing
• Selecting/Accessing sub-array by giving only stop value
• Selecting/Accessing sub-array by giving only the start value

## Method 1 − Selecting a single NumPy array element

Each element of these ndarrays can be accessed by their index number.

### Algorithm (Steps)

Following are the Algorithm/steps to be followed to perform the desired task −

• Use the import keyword, to import the numpy module with an alias name(np).

• Use the numpy.array() function(returns a ndarray. The ndarray is an array object that satisfies the given requirements), for creating a numpy array by passing the 1-Dimensional array as an argument to it.

• Use positive indexing to access the NumPy array element at index 1 and print it.

• Use negative indexing to access the NumPy array element at index -1 i.e the last element of an array and print it.

Negative Indexing():
Python allows for "indexing from the end," i.e., negative indexing.
This means that the last value in a sequence has an index of -1, the
second last has an index of -2, and so on.
When you want to pick values from the end (right side) of an iterable, you
can utilize negative indexing to your benefit.

### Example

The following program returns the elements at the specified index from an input NumPy array using index number −

# importing numpy module with an alias name
import numpy as np

# creating a 1-Dimensional NumPy array
inputArray = np.array([4, 5, 1, 2, 8])

# printing the array element at index 1 (positive indexing)
print("The input array = ",inputArray)
print("Numpy array element at index 1:", inputArray)

# printing the array element at index -1 i.e last element (negative indexing)
print("Numpy array element at index -1(last element):", inputArray[-1])


### Output

On executing, the above program will generate the following output −

The input array =  [4 5 1 2 8]
Numpy array element at index 1: 5
Numpy array element at index -1(last element): 8


## Method 2 − Selecting a sub-array from a NumPy array using slicing

In order to obtain a sub-array, we replace a slice in place of the element index.

### Syntax

numpyArray[start:stop]


Where, start, stop are the first and last indexes of the sub-array respectively.

### Algorithm (Steps)

Following are the Algorithm/steps to be followed to perform the desired task −

• Use the numpy.array() function(returns a ndarray. The ndarray is an array object that satisfies the given requirements), for creating a NumPy array by passing the 1-Dimensional array as an argument to it.

• Access the sub-array from index 2 to 5(excluded) by giving start, and stop values using slicing and printing it.

### Example

The following program returns the sub-array from an input NumPy array using slicing by giving both the start, and stop values −

# importing NumPy module with an alias name
import numpy as np

# creating a 1-Dimensional numpy array
inputArray = np.array([4, 5, 1, 2, 8, 9, 7])
print("Input Array =",inputArray)

# printing the sub-array from index 2 to 5(excluded) by giving start, stop values
print("The sub-array from index 2 to 5(excluded)=", inputArray[2:5])


### Output

On executing, the above program will generate the following output −

Input Array = [4 5 1 2 8 9 7]
The sub-array from index 2 to 5(excluded)= [1 2 8]


## Method 3 − Selecting/Accessing sub-array by giving only stop value

By leaving the starting index blank, you can slice a sub-array starting from the first element.

It takes the start value as 0 by default.

### Example

The following program returns the sub-array from an input NumPy array from index 0(default) to the given stop value −

# importing NumPy module with an alias name
import numpy as np

# creating a 1-Dimensional NumPy array
inputArray = np.array([4, 5, 1, 2, 8, 9, 7])
print("Input Array =",inputArray)

# printing the sub-array till index 5(excluded) by giving only stop value

# it starts from index 0 by default
print("The sub-array till index 5(excluded)=", inputArray[:5])


### Output

On executing, the above program will generate the following output −

Input Array = [4 5 1 2 8 9 7]
The sub-array till index 5(excluded)= [4 5 1 2 8]


## Method 4 − Selecting/Accessing sub-array by giving only the start value

Similarly, leaving the left side of the colon blank will give you an array up to the last element.

### Example

The following program returns the sub-array from an input NumPy array from a given start index value till the last index(default) of an array.

# importing NumPy module with an alias name
import numpy as np

# creating a 1-Dimensional NumPy array
inputArray = np.array([4, 5, 1, 2, 8, 9, 7])

# printing the sub-array from index 2 to the last index by giving only the start value
print("Input Array = ",inputArray)
# It extends till the last index value by default
print("The sub-array till index 5(excluded)=", inputArray[2:])


### Output

On executing, the above program will generate the following output −

Input Array = [4 5 1 2 8 9 7]
The sub-array till index 5(excluded)= [1 2 8 9 7]


## Conclusion

We learned how to select elements of a numpy array in Python using four different examples in this article. We also learned about slice Numpy Arrays.