is_any_int_dtype(arr_or_dtype) -> 'bool'
In this function, timedelta64 instances are also considered "any-integer" type objects and will return True.
This function is internal and should not be exposed in the public API.
The nullable Integer dtypes (e.g. pandas.Int64Dtype) are also considered as integer by this function.
The array or dtype to check.
Whether or not the array or dtype is of an integer dtype.
Check whether the provided array or dtype is of an integer dtype.
>>> is_any_int_dtype(str) FalseThis example is valid syntax, but we were not able to check execution
>>> is_any_int_dtype(int) TrueThis example is valid syntax, but we were not able to check execution
>>> is_any_int_dtype(float) FalseThis example is valid syntax, but we were not able to check execution
>>> is_any_int_dtype(np.uint64) TrueThis example is valid syntax, but we were not able to check execution
>>> is_any_int_dtype(np.datetime64) FalseThis example is valid syntax, but we were not able to check execution
>>> is_any_int_dtype(np.timedelta64) TrueThis example is valid syntax, but we were not able to check execution
>>> is_any_int_dtype(np.array(['a', 'b'])) FalseThis example is valid syntax, but we were not able to check execution
>>> is_any_int_dtype(pd.Series([1, 2])) TrueThis example is valid syntax, but we were not able to check execution
>>> is_any_int_dtype(np.array([], dtype=np.timedelta64)) TrueThis example is valid syntax, but we were not able to check execution
>>> is_any_int_dtype(pd.Index([1, 2.])) # float FalseSee :
The following pages refer to to this document either explicitly or contain code examples using this.
pandas.core.dtypes.common.is_any_int_dtype
pandas.core.dtypes.common.is_signed_integer_dtype
pandas.core.dtypes.common.is_integer_dtype
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