dchvn commented on a change in pull request #34778:
URL: https://github.com/apache/spark/pull/34778#discussion_r760795723
##########
File path: python/pyspark/pandas/tests/test_dataframe.py
##########
@@ -5870,8 +5870,12 @@ def test_cov(self):
self.assert_eq(pdf.cov(min_periods=5), psdf.cov(min_periods=5))
# extension dtype
- numeric_dtypes = ["Int8", "Int16", "Int32", "Int64", "Float32",
"Float64", "float"]
- boolean_dtypes = ["boolean", "bool"]
+ if LooseVersion(pd.__version__) >= LooseVersion("1.2"):
Review comment:
with pandas < 1.2, `pd.Dataframe.cov` can not work with extension dtype
`NAType`, so I just fix the test only
```python
>>> pd.__version__
'1.0.5'
>>> pdf = pd.DataFrame([[1,2],[None, 3]], dtype="Int64")
>>> pdf
0 1
0 1 2
1 <NA> 3
>>> pdf.cov()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File
"/u02/venv/python3.8/lib/python3.8/site-packages/pandas/core/frame.py", line
7608, in cov
baseCov = libalgos.nancorr(ensure_float64(mat), cov=True,
minp=min_periods)
File "pandas/_libs/algos_common_helper.pxi", line 41, in
pandas._libs.algos.ensure_float64
TypeError: float() argument must be a string or a number, not 'NAType'
```
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