In Python, how could you check if the type of a number is an integer without checking each integer type, i.e., 'int'
, 'numpy.int32'
, or 'numpy.int64'
?
I thought to try if int(val) == val
but this does not work when a float is set to an integer value (not type).
In [1]: vals = [3, np.ones(1, dtype=np.int32)[0], np.zeros(1, dtype=np.int64)[0], np.ones(1)[0]]
In [2]: for val in vals:
...: print(type(val))
...: if int(val) == val:
...: print('{} is an int'.format(val))
<class 'int'>
3 is an int
<class 'numpy.int32'>
1 is an int
<class 'numpy.int64'>
0 is an int
<class 'numpy.float64'>
1.0 is an int
I want to filter out the last value, which is a numpy.float64
.
You can use isinstance
with a tuple argument containing the types of interest.
To capture all python and numpy integer types use:
isinstance(value, (int, np.integer))
Here is an example showing the results for several data types:
vals = [3, np.int32(2), np.int64(1), np.float64(0)]
[(e, type(e), isinstance(e, (int, np.integer))) for e in vals]
Result:
[(3, <type 'int'>, True),
(2, <type 'numpy.int32'>, True),
(1, <type 'numpy.int64'>, True),
(0.0, <type 'numpy.float64'>, False)]
A second example which is true only for int and int64:
[(e, type(e), isinstance(e, (int, np.int64))) for e in vals]
Result:
[(3, <type 'int'>, True),
(1, <type 'numpy.int32'>, False),
(0, <type 'numpy.int64'>, True),
(0.0, <type 'numpy.float64'>, False)]
In addition to the accepted answer, the standard library also provides the numbers
module, which defines abstract classes for numerical types that can be used with isinstance
:
isinstance(value, numbers.Integral)
This can be used to recognize both Python's int
as well as NumPy's np.int64
.
Use np.issubdtype
:
for val in vals:
if isinstance(val, int) or np.issubdtype(val, np.int):
print('{} is an int'.format(val))
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