Get Row Numbers of NumPy Array having Element Larger than X
Last Updated :
29 Sep, 2025
The task is to find the row indices of an array where at least one element is greater than a given threshold X.
For Example: Given array [[1, 5], [7, 2], [3, 9]] and X = 6 and goal is to identify the rows that contain values greater than 6.
Python
import numpy as np
arr = np.array([[1, 5], [7, 2], [3, 9]])
X = 6
res = np.where(np.any(arr > X, axis=1))
print(res)
Explanation:
- arr > X creates a boolean array.
- np.any(..., axis=1) checks each row for at least one value > 6.
- np.where(...) gives row indices -> here rows 1 and 2.
Syntax
numpy.where()
numpy.where(condition[, x, y])
Parameters:
- condition: Boolean expression to evaluate.
- x, y (optional): Values to pick depending on whether the condition is True or False.
Return Value: Indices where condition holds true or array built from x and y.
numpy.any()
numpy.any(a, axis=None, out=None, keepdims=False)
Parameters:
- a: Input array.
- axis: Axis along which to evaluate condition (axis=1 checks row-wise).
- out: Optional output array.
- keepdims: Whether to keep reduced dimensions.
Return Value: Boolean result or array indicating if any condition is True.
Examples
Example 1: In this example, we create a 2D NumPy array and check which rows contain at least one element larger than a specified value X.
Python
import numpy as np
arr = np.array([[1, 2, 3, 4, 5],
[10, -3, 30, 4, 5],
[3, 2, 5, -4, 5],
[9, 7, 3, 6, 5]])
X = 6 # declare threshold value
print("Array:")
print(arr)
res = np.where(np.any(arr > X, axis=1)) # find row numbers where at least one element > X
print("Result:")
print(res)
OutputArray:
[[ 1 2 3 4 5]
[10 -3 30 4 5]
[ 3 2 5 -4 5]
[ 9 7 3 6 5]]
Result:
(array([1, 3]),)
Explanation
- arr > X: Creates a boolean array marking values greater than X.
- np.any(.., axis=1): Checks each row to see if at least one element is True.
- np.where(...): Returns indices of rows where the condition holds.
- Here, rows 1 and 3 contain elements larger than 6, so their indices are returned.
Example 2: In this example, we use a different 2D array and find rows that have elements larger than 15.
Python
import numpy as np
arr = np.array([[5, 8, 12], [20, 3, 9], [7, 14, 18], [2, 10, 6]])
X = 15 # declare threshold value
print("Array:")
print(arr)
res = np.where(np.any(arr > X, axis=1)) # find row numbers where at least one element > X
print("Result:")
print(res)
OutputArray:
[[ 5 8 12]
[20 3 9]
[ 7 14 18]
[ 2 10 6]]
Result:
(array([1, 2]),)
Explanation:
- arr > X: Marks elements greater than 15.
- np.any(..., axis=1): Checks row-wise for any True.
- np.where(...): Returns row indices with elements exceeding 15.
- Rows 1 and 2 contain values above 15, so their indices are returned.
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