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 Arrays in Python

As the name suggests, NumPy arrays are the central data structure of the NumPy library. The name of the library is an abbreviation of "Numeric Python" or "Numerical Python".

In other words, NumPy is a Python library that is the foundation for scientific computing in Python. One such tool is the high-performance multidimensional array object, a powerful data structure for efficient array and matrix calculations.

We can select one element or a subarray from a Numpy array at a time. Now we see the following method for selecting elements from a Numpy array.

• Selecting a single NumPy array element
• Using slicing to select subarrays from NumPy arrays
• Select/access subarray only by giving stop value
• Select/access subarray only by giving starting value

Method 1 - Selecting a Single NumPy Array Element

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

Algorithm (steps)

The following are the algorithms/steps that need to be followed to perform the required task -

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

• Use the numpy.array() function (which returns an ndarray. An ndarray is an array object that meets the given requirements) to create a numpy array of arrays by passing a one-dimensional array as its argument.

• Use positive indexingAccess 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 element at a specified index from an input NumPy array using the 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[1])

# 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

When executed, 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 - Using Slicing to Select Subarrays from NumPy Arrays

To obtain subarrays, we use slices instead of element indexes.

grammar

numpyArray[start:stop]

Among them, start and stop are the first and last index of the subarray respectively.

Algorithm (steps)

The following are the algorithms/steps that need to be followed to perform the required task -

• Use the numpy.array() function (which returns an ndarray. An ndarray is an array object that meets the given requirements) to create a numpy array of arrays by passing a one-dimensional array as its argument.

• Access the subarray from index 2 to 5 (exclusive) by giving the start value and the end value using slicing and printing it.

Example

The following program uses slicing to return a subarray from an input NumPy array by giving a start value and a 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 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

When executed, 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 - Select/access subarray by giving only stop value

You can slice the subarray starting from the first element by leaving the starting index blank.

The default starting value is 0.

Example

The following program returns a subarray of the 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

When executed, 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 - Select/access subarray by giving only starting value

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

Example

The following program returns a subarray of an input NumPy array from a given starting index value to the last index of the array (the default).

# 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

When executed, 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]

in conclusion

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

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