My first SO question:
I am confused about this behavior of apply method of groupby in pandas (0.12.0-4), it appears to apply the function TWICE to the first row of a data frame. For example:
>>> from pandas import Series, DataFrame
>>> import pandas as pd
>>> df = pd.DataFrame({'class': ['A', 'B', 'C'], 'count':[1,0,2]})
>>> print(df)
class count
0 A 1
1 B 0
2 C 2
I first check that the groupby function works ok, and it seems to be fine:
>>> for group in df.groupby('class', group_keys = True):
>>> print(group)
('A', class count
0 A 1)
('B', class count
1 B 0)
('C', class count
2 C 2)
Then I try to do something similar using apply on the groupby object and I get the first row output twice:
>>> def checkit(group):
>>> print(group)
>>> df.groupby('class', group_keys = True).apply(checkit)
class count
0 A 1
class count
0 A 1
class count
1 B 0
class count
2 C 2
Any help would be appreciated! Thanks.
Edit: @Jeff provides the answer below. I am dense and did not understand it immediately, so here is a simple example to show that despite the double printout of the first group in the example above, the apply method operates only once on the first group and does not mutate the original data frame:
>>> def addone(group):
>>> group['count'] += 1
>>> return group
>>> df.groupby('class', group_keys = True).apply(addone)
>>> print(df)
class count
0 A 1
1 B 0
2 C 2
But by assigning the return of the method to a new object, we see that it works as expected:
>>> df2 = df.groupby('class', group_keys = True).apply(addone)
>>> print(df2)
class count
0 A 2
1 B 1
2 C 3
question from:
https://stackoverflow.com/questions/21390035/pandas-groupby-apply-method-duplicates-first-group 与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…