t_values = df_grouped_by_day.sort_values('day_of_week').groupby(['day_of_week', 'day_of_week_name'])['Show_up'].apply(lambda sample: ttest_ind(population, sample)).reset_index()
到目前为止,我想出的最胜利的方法是:
t_values = (df_grouped_by_day
.sort_values('day_of_week')
.groupby(['day_of_week', 'day_of_week_name'])['Show_up']
.apply(lambda sample: ttest_ind(population, sample))
.reset_index())
\
可以放在线的末端,除了最后一个。
t_values = df_grouped_by_day \
.sort_values('day_of_week') \
.groupby(['day_of_week', 'day_of_week_name'])['Show_up'] \
.apply(lambda sample: ttest_ind(population, sample)) \
.reset_index()
t_values = df_grouped_by_day.sort_values('day_of_week'
).groupby(['day_of_week', 'day_of_week_name']
)['Show_up'
].apply(lambda sample: ttest_ind(population, sample)
).reset_index())
pypythonblack包裹了call链条的线条:
t_values = (
df_grouped_by_day.sort_values('day_of_week')
.groupby(
[
'day_of_week',
'day_of_week_name',
"foo",
"bar",
"buzz",
"foobar",
"foobarbuz",
]
)['Show_up']
.apply(
lambda sample: ttest_ind(
population,
sample,
foo,
bar,
buzz,
foobar,
foobarbuz,
)
)
.reset_index()
)
i我添加了更多参数,以扩展上述示例,但减少了它们以使我的观点在下面的一个中。
以个人的方式,我曾经更喜欢以下内容,但是在没有参数的一些呼叫以及混合方形 - 布拉斯附件语法时,这可能会变得很奇怪,就像上面的示例一样。t_values = df_grouped_by_day.sort_values(
'day_of_week',
).groupby(
[
'day_of_week',
'day_of_week_name',
]
).apply(
lambda sample: ttest_ind(population, sample)
)