How to check whether specified values are present in NumPy array?

NumPy provides several methods to check whether specified values are present in an array. The most common approaches are using the in keyword, np.isin() function, and np.where() function.

Using the "in" Keyword

The in keyword checks if a single element exists in the array ?

import numpy as np

arr = np.array([10, 30, 2, 40.3, 56, 456, 32, 4])
print("The Original array:", arr)

if 4 in arr:
    print("The element 4 is present in the array.")
else:
    print("The element 4 is not present in the array.")

The Original array: [ 10.   30.    2.   40.3  56.  456.   32.    4. ]
The element 4 is present in the array.

Checking Multiple Values

To check multiple values, use separate in statements ?

import numpy as np

arr = np.array([10, 30, 2, 40.3, 56, 4, 56, 3, 2, 4])
print("The Original array:", arr)

if 4 in arr and 56 in arr:
    print("Both elements 4 and 56 are present in the array.")
else:
    print("One or both elements are not present in the array.")

The Original array: [10.  30.   2.  40.3 56.   4.  56.   3.   2.   4. ]
Both elements 4 and 56 are present in the array.

Using np.isin() Function

The np.isin() function returns a boolean array showing which elements match the specified values ?

import numpy as np

arr = np.array([[10, 30, 2, 40.3], [56, 4, 56, 3]])
print("The Original array:")
print(arr)

values = np.array([10, 30, 2, 40.3])
result = np.isin(arr, values)
print("\nBoolean result:")
print(result)

print("\nAny matches found:", np.any(result))

The Original array:
[[10.  30.   2.  40.3]
 [56.   4.  56.   3. ]]

Boolean result:
[[ True  True  True  True]
 [False False False False]]

Any matches found: True

3D Array Example

import numpy as np

arr = np.array([[[10, 30], [2, 40.3]], [[56, 4], [56, 3]]])
print("The Original array:")
print(arr)

values = np.array([1, 40.3])
result = np.isin(arr, values)
print("\nBoolean result:")
print(result)

The Original array:
[[[10.  30. ]
  [ 2.  40.3]]

 [[56.   4. ]
  [56.   3. ]]]

Boolean result:
[[[False False]
  [False  True]]

 [[False False]
  [False False]]]

Using np.where() Function

The np.where() function returns the indices where the condition is true ?

import numpy as np

arr = np.array([[[10, 30], [2, 40.3]], [[56, 4], [56, 3]]])
print("The Original array:")
print(arr)

indices = np.where(arr == 3)
print("\nIndices where value is 3:")
print(indices)

if len(indices[0]) > 0:
    print("Value 3 found at positions:", list(zip(*indices)))
else:
    print("Value 3 not found in the array")

The Original array:
[[[10.  30. ]
  [ 2.  40.3]]

 [[56.   4. ]
  [56.   3. ]]]

Indices where value is 3:
(array([1]), array([1]), array([1]))
Value 3 found at positions: [(1, 1, 1)]

Comparison

Conclusion

Use in for simple single value checks, np.isin() for multiple values or element-wise comparisons, and np.where() when you need to find the exact positions of matching elements.