﻿ NumPy: Find and store non-zero unique rows in an array after comparing each row with other row in a given matrix - w3resource # NumPy: Find and store non-zero unique rows in an array after comparing each row with other row in a given matrix

## NumPy: Array Object Exercise-172 with Solution

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:

``````import numpy as np
arra = np.array([[ 1,  1,  0],
[ 0,  0,  0],
[ 0,  2,  3],
[ 0,  0,  0],
[ 0, -1,  1],
[ 0,  0,  0]])

print("Original array:")
print(arra)
temp = {(0, 0, 0)}
result = []
for idx, row in enumerate(map(tuple, arra)):
if row not in temp:
result.append(idx)
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]]
```

Pictorial Presentation: Python Code Editor:

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## Python: Tips of the Day

Set comprehension:

```>>> m = {x ** 2 for x in range(5)}
>>> m
{0, 1, 4, 9, 16}
```