The behavior of the Series functions changes when I introduced a np.nan in the series. But Pandas seem to handle this just fine. Some of the functions and their outputs.
def usingSeries():
s = ks.Series([11, 3, 5, 6, 8,np.nan])
print(s.max())
print(s.min())
print(s.kurtosis())
print(s.std())
nan
3.0
nan
nan
def usingPdSeries():
s = pd.Series([11, 3, 5, np.nan, 6, 8])
print(s.max())
print(s.min())
print(s.kurtosis())
print(s.std())
11.0
3.0
-0.0034686090877542597
3.049590136395381
Thanks for reporting!
When running
s = ks.Series([11, 3, 5, 6, 8, np.nan])
print(s.max())
print(s.min())
print(s.kurtosis())
print(s.std())
with Koalas 0.2, I get the following output:
11.0
3.0
-1.0008671522719388
3.0495901363953815
Has this issue been fixed with the latest Koalas release or is something wrong with @akhilanandbv003's setup?
It works fine for me.
>>> s = ks.Series([11, 3, 5, 6, 8, np.nan])
>>> print(s.max())
11.0
>>> print(s.min())
3.0
>>> print(s.kurtosis())
-1.0008671522719395
>>> print(s.std())
3.0495901363953815
I also confirmed that it works fine. Closing this. Thank you guys.
Thanks for the update. I was getting that behavior with 0.1. Didn’t get a
chance to try with 0.2 release though.
On Fri, May 3, 2019 at 3:41 AM Hyukjin Kwon notifications@github.com
wrote:
Closed #208 https://github.com/databricks/koalas/issues/208.
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Most helpful comment
When running
with Koalas 0.2, I get the following output:
Has this issue been fixed with the latest Koalas release or is something wrong with @akhilanandbv003's setup?