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Implement Series.pop #789

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HyukjinKwon opened this issue Sep 17, 2019 · 6 comments · Fixed by #866
Closed

Implement Series.pop #789

HyukjinKwon opened this issue Sep 17, 2019 · 6 comments · Fixed by #866
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enhancement New feature or request

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@HyukjinKwon
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HyukjinKwon commented Sep 17, 2019 •
edited

filter out given arugmnet in the series. See https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.pop.html?highlight=pop#pandas.Series.pop

Related to #362
@HyukjinKwon HyukjinKwon added the enhancement New feature or request label Sep 17, 2019
@HyukjinKwon
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cc @itholic and @harupy are you interested in it?

@itholic
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itholic commented Sep 17, 2019

@HyukjinKwon Oh it looks interesting. i'll try this out :)

@harupy
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harupy commented Sep 17, 2019

pandas.DataFrame.pop and pandas.Series.pop use the same function internally.

https://github.com/pandas-dev/pandas/blob/v0.25.1/pandas/core/generic.py#L821-L869

@harupy
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harupy commented Sep 17, 2019

And they both have the exact same doc.

@HyukjinKwon
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Yes i checked that too but from my cursory look, we cannot share implementation in Koalas. In this case, it might better to have two separate APIs with two separate examples. It's fine to have some differences if that looks obviously better.

@itholic
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itholic commented Sep 23, 2019

i'm working on this.

@itholic itholic mentioned this issue Oct 3, 2019
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HyukjinKwon pushed a commit that referenced this issue Nov 22, 2019
@itholic @HyukjinKwon
Implement Series.pop (#866)
dad31db 
Resolves #789 

```python
>>> s = ks.Series(data=np.arange(3), index=['A', 'B', 'C'])
>>> s
A    0
B    1
C    2
Name: 0, dtype: int64

>>> s.pop('A')
A    0
Name: 0, dtype: int64

>>> s
B    1
C    2
Name: 0, dtype: int64
```

Also support for MultiIndex

```python
>>> midx = pd.MultiIndex([['lama', 'cow', 'falcon'],
...                       ['speed', 'weight', 'length']],
...                      [[0, 0, 0, 1, 1, 1, 2, 2, 2],
...                       [0, 1, 2, 0, 1, 2, 0, 1, 2]])
>>> s = ks.Series([45, 200, 1.2, 30, 250, 1.5, 320, 1, 0.3],
...               index=midx)
>>> s
lama    speed      45.0
        weight    200.0
        length      1.2
cow     speed      30.0
        weight    250.0
        length      1.5
falcon  speed     320.0
        weight      1.0
        length      0.3
Name: 0, dtype: float64

>>> s.pop('lama')
lama  speed      45.0
      weight    200.0
      length      1.2
Name: 0, dtype: float64

>>> s
cow     speed      30.0
        weight    250.0
        length      1.5
falcon  speed     320.0
        weight      1.0
        length      0.3
Name: 0, dtype: float64
```

And beyond pandas, we can support for MultiIndex with specifying level.
(But i'm not sure this is necessary.)

```python
>>> midx = pd.MultiIndex([['lama', 'cow', 'falcon'],
...                       ['speed', 'weight', 'length']],
...                      [[0, 0, 0, 1, 1, 1, 2, 2, 2],
...                       [0, 1, 2, 0, 1, 2, 0, 1, 2]])
>>> s = ks.Series([45, 200, 1.2, 30, 250, 1.5, 320, 1, 0.3],
...               index=midx)
>>> s
lama    speed      45.0
        weight    200.0
        length      1.2
cow     speed      30.0
        weight    250.0
        length      1.5
falcon  speed     320.0
        weight      1.0
        length      0.3
Name: 0, dtype: float64

>>> s.pop('speed', level=1)
lama    speed     45.0
cow     speed     30.0
falcon  speed    320.0
Name: 0, dtype: float64

>>> s
lama    weight    200.0
        length      1.2
cow     weight    250.0
        length      1.5
falcon  weight      1.0
        length      0.3
Name: 0, dtype: float64
```

In pandas, above example raises TypeError like below:

```python
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: pop() got an unexpected keyword argument 'level'
```
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Implement Series.pop itholic/koalas
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@HyukjinKwon @harupy @itholic