NumPy: Find and store non-zero unique rows in an array after comparing each row with other row in a given matrix

Last update on April 26 2025 12:40:36 (UTC/GMT +8 hours)

Store non-zero unique rows from a matrix.

Write a NumPy program to find and store non-zero unique rows in an array after comparing each row with other row in a given matrix.

Sample Solution:

Python Code:

# Importing NumPy library
import numpy as np

# Creating a NumPy array
arra = np.array([[1, 1, 0],
                 [0, 0, 0],
                 [0, 2, 3],
                 [0, 0, 0],
                 [0, -1, 1],
                 [0, 0, 0]])

# Printing the original array
print("Original array:")
print(arra)

# Creating a set of tuples with all zeros
temp = {(0, 0, 0)}

# Initializing an empty list to store row indices
result = []

# Enumerating through each row as a tuple and its index
for idx, row in enumerate(map(tuple, arra)):
    # Checking if the row is not in the set of all zeros
    if row not in temp:
        # Appending the index to the result list
        result.append(idx)

# Printing non-zero unique rows based on their indices
print("\nNon-zero unique rows:")
print(arra[result])

Sample Output:

Original array:
[[ 1  1  0]
 [ 0  0  0]
 [ 0  2  3]
 [ 0  0  0]
 [ 0 -1  1]
 [ 0  0  0]]

Non-zero unique rows:
[[ 1  1  0]
 [ 0  2  3]
 [ 0 -1  1]]

Explanation:

In the above exercise -

• arra = np.array(...): This line creates a 6x3 NumPy array.
• temp = {(0, 0, 0)}: Creates a set containing the tuple (0, 0, 0) which we want to remove from arra.
• result = []: This line initializes an empty list that will store the indices of rows in arra that don't match the given tuple.
• for idx, row in enumerate(map(tuple, arra)): The for loop iterates through the enumerated rows of ‘arra’ after converting each row to a tuple using map(tuple, arra).
• if row not in temp: checks if the current row (as a tuple) is not in the set temp (i.e., not equal to (0, 0, 0)).
• If the condition is True, the index (idx) of the current row is appended to the result list.
• After the loop, arra[result] selects rows of arra using the indices stored in the result list, effectively removing rows that matched the given tuple.
• Finally print() function prints the modified array ‘arra’, with all rows containing (0, 0, 0) removed.

Pictorial Presentation:

For more Practice: Solve these Related Problems:

• Write a NumPy program to extract rows from a 2D array that are non-zero and unique using np.unique with axis=0.
• Create a function that filters out rows that contain all zeros before identifying unique rows.
• Implement a solution that first removes duplicate rows and then excludes any rows containing only zero elements.
• Test the function on matrices with intermittent zero rows to ensure correct extraction of unique, non-zero rows.

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