itholic commented on a change in pull request #33757:
URL: https://github.com/apache/spark/pull/33757#discussion_r690877203
##########
File path: python/pyspark/pandas/tests/data_type_ops/test_categorical_ops.py
##########
@@ -183,22 +183,31 @@ def test_astype(self):
psser = ps.from_pandas(pser)
self.assert_eq(pser.astype(int), psser.astype(int))
self.assert_eq(pser.astype(float), psser.astype(float))
- self.assert_eq(pser.astype(np.float32), psser.astype(np.float32))
- self.assert_eq(pser.astype(np.int32), psser.astype(np.int32))
- self.assert_eq(pser.astype(np.int16), psser.astype(np.int16))
- self.assert_eq(pser.astype(np.int8), psser.astype(np.int8))
self.assert_eq(pser.astype(str), psser.astype(str))
- self.assert_eq(pser.astype(bool), psser.astype(bool))
self.assert_eq(pser.astype("category"), psser.astype("category"))
+ # Bug in pandas 1.2
+ if (LooseVersion(pd.__version__) >= LooseVersion("1.2")) and (
+ LooseVersion(pd.__version__) < LooseVersion("1.3")
+ ):
+ self.assert_eq(psser.astype(np.float32), ps.Series(data,
dtype=np.float32))
+ self.assert_eq(psser.astype(np.int32), ps.Series(data,
dtype=np.int32))
+ self.assert_eq(psser.astype(np.int16), ps.Series(data,
dtype=np.int16))
+ self.assert_eq(psser.astype(np.int8), ps.Series(data,
dtype=np.int8))
+ self.assert_eq(psser.astype(bool), ps.Series(data, dtype=bool))
+ else:
+ self.assert_eq(pser.astype(np.float32), psser.astype(np.float32))
+ self.assert_eq(pser.astype(np.int32), psser.astype(np.int32))
+ self.assert_eq(pser.astype(np.int16), psser.astype(np.int16))
+ self.assert_eq(pser.astype(np.int8), psser.astype(np.int8))
+ self.assert_eq(pser.astype(bool), psser.astype(bool))
Review comment:
Oh... then seems like we're missing tests for pandas 1.2 ??
It's failed on my local with pandas 1.2.
```
Attribute "dtype" are different
[left]: float64
[right]: float32
Left:
0 1.0
1 2.0
2 3.0
dtype: float64
float64
Right:
0 1.0
1 2.0
2 3.0
dtype: float32
float32
```
The result is actually different.
```python
>>> pd.__version__
'1.2.0'
>>> pser.astype(np.float32)
0 1.0
1 2.0
2 3.0
dtype: float64
>>> psser.astype(np.float32)
0 1.0
1 2.0
2 3.0
dtype: float32
```
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