How to check whether specified values are present in NumPy array?
Last Updated :
22 Sep, 2020
Sometimes we need to test whether certain values are present in an array. Using Numpy array, we can easily find whether specific values are present or not. For this purpose, we use the “in” operator. “in” operator is used to check whether certain element and values are present in a given sequence and hence return Boolean values ‘True” and “False“.
Example 1:
Python3
import numpy as np
n_array = np.array([[ 2 , 3 , 0 ],
[ 4 , 1 , 6 ]])
print ( "Given array:" )
print (n_array)
print ( 2 in n_array)
print ( 0 in n_array)
print ( 6 in n_array)
print ( 50 in n_array)
print ( 10 in n_array)
|
Output:
Given array:
[[2 3 0]
[4 1 6]]
True
True
True
False
False
In the above example, we check whether values 2, 0, 6, 50, 10 are present in Numpy array ‘n_array‘ using the ‘in‘ operator.
Example 2:
Python3
import numpy as np
n_array = np.array([[ 2.14 , 3 , 0.5 ],
[ 4.5 , 1.2 , 6.2 ],
[ 20.2 , 5.9 , 8.8 ]])
print ( "Given array:" )
print (n_array)
print ( 2.14 in n_array)
print ( 5.28 in n_array)
print ( 6.2 in n_array)
print ( 5.9 in n_array)
print ( 8.5 in n_array)
|
Output:
Given array:
[[ 2.14 3. 0.5 ]
[ 4.5 1.2 6.2 ]
[20.2 5.9 8.8 ]]
True
False
True
True
False
In the above example, we check whether values 2.14, 5.28, 6.2, 5.9, 8.5 are present in Numpy array ‘n_array‘.
Example 3:
Python3
import numpy as np
n_array = np.array([[ 4 , 5.5 , 7 , 6.9 , 10 ],
[ 7.1 , 5.3 , 40 , 8.8 , 1 ],
[ 4.4 , 9.3 , 6 , 2.2 , 11 ],
[ 7.1 , 4 , 5 , 9 , 10.5 ]])
print ( "Given array:" )
print (n_array)
print ( 2.14 in n_array)
print ( 5.28 in n_array)
print ( 8.5 in n_array)
|
Output:
Given array:
[[ 4. 5.5 7. 6.9 10. ]
[ 7.1 5.3 40. 8.8 1. ]
[ 4.4 9.3 6. 2.2 11. ]
[ 7.1 4. 5. 9. 10.5]]
False
False
False
In the above example, we check whether values 2.14, 5.28, 8.5 are present in Numpy array ‘n_array‘.
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