jorisvandenbossche commented on code in PR #34184:
URL: https://github.com/apache/arrow/pull/34184#discussion_r1119737972
##########
python/pyarrow/_compute.pyx:
##########
@@ -2436,6 +2436,19 @@ cdef class Expression(_Weakrefable):
options = NullOptions(nan_is_null=nan_is_null)
return Expression._call("is_null", [self], options)
+ def is_nan(self):
+ """
+ Check whether the expression is nan.
Review Comment:
```suggestion
Check whether the expression is NaN.
```
##########
python/pyarrow/array.pxi:
##########
@@ -1253,6 +1253,16 @@ cdef class Array(_PandasConvertible):
options = _pc().NullOptions(nan_is_null=nan_is_null)
return _pc().call_function('is_null', [self], options)
+ def is_nan(self):
+ """
+ Return BooleanArray indicating the nan values.
+
+ Returns
+ -------
+ array : boolean Array, where null values are None
Review Comment:
What does this "where null values are None" mean exactly?
##########
python/pyarrow/array.pxi:
##########
@@ -1253,6 +1253,16 @@ cdef class Array(_PandasConvertible):
options = _pc().NullOptions(nan_is_null=nan_is_null)
return _pc().call_function('is_null', [self], options)
+ def is_nan(self):
+ """
+ Return BooleanArray indicating the nan values.
Review Comment:
```suggestion
Return BooleanArray indicating the NaN values.
```
##########
python/pyarrow/tests/test_compute.py:
##########
@@ -1635,6 +1636,23 @@ def test_is_null():
assert result.equals(expected)
+def test_is_nan():
+ arr = pa.array([1, 2, 3, None, np.nan])
+ result = arr.is_nan()
+ expected = pa.array([False, False, False, None, True])
+ assert result.equals(expected)
+
+ with pytest.raises(
+ ArrowNotImplementedError, match="has no kernel matching input
types"):
+ arr = pa.array(["1", "2", None], type=pa.string())
Review Comment:
```suggestion
arr = pa.array(["1", "2", None], type=pa.string())
with pytest.raises(
ArrowNotImplementedError, match="has no kernel matching input
types"):
```
And the same for the one below (although unlikely here, but that avoids that
it might be accidentally the array creation that is erroring, instead of
calling is_nan)
##########
python/pyarrow/table.pxi:
##########
@@ -327,6 +327,32 @@ cdef class ChunkedArray(_PandasConvertible):
options = _pc().NullOptions(nan_is_null=nan_is_null)
return _pc().call_function('is_null', [self], options)
+ def is_nan(self):
+ """
+ Return boolean array indicating the nan values.
Review Comment:
```suggestion
Return boolean array indicating the NaN values.
```
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