[英]pandas groupby with a lambda parameter
I can't understand the code: 我不明白代码:
pivot = pd.pivot_table(subset, values='count', rows=['date'], cols=['sample'], fill_value=0)
by = lambda x: lambda y: getattr(y, x)
grouped = pivot.groupby([by('year'),by('month')]).sum()
subset
in the code is a DataFrame which have a column named "date"(eg2013-02-04 06:20:49.634244), and do not have a column named "year" and "month". 代码中的
subset
是一个DataFrame,它具有一个名为“日期”的列(例如,2013-02-04 06:20:49.634244),而没有一个名为“年”和“月”的列。
where I have trouble with
我有麻烦的地方
I can't figure out the "year" and "month" in: 我无法确定“年”和“月”的形式:
grouped = pivot.groupby([by('year'),by('month')]).sum()
What the meaning of 是什么意思
grouped = pivot.groupby([by('year'),by('month')]).sum()
What I have done:
我做了什么:
In the pandas pandas document says: the first parame of the pandas.DataFrame.groupby can be 在pandas中pandas文档说:pandas.DataFrame.groupby的第一个参数可以是
by : mapping function / list of functions, dict, Series, or tuple /
作者:映射函数/函数列表,字典,系列或元组/
by = lambda x: lambda y: getattr(y, x) 由= lambda x:lambda y:getattr(y,x)
means by('bar') returns a function that returns the attribute 'bar' from an object
表示by('bar')返回一个函数,该函数从对象返回属性'bar'
If a callable is passed to groupby
, it is called on the DataFrame
's index, so this code is is grouping by the year and month of a datetimelike index. 如果将callable传递给
groupby
,则会在DataFrame
的索引上调用它,因此此代码DataFrame
datetimelike索引的年和月进行分组。
In [55]: df = pd.DataFrame({'a': 1.0},
index=pd.date_range('2014-01-01', periods=13, freq='M'))
In [56]: df.groupby([by('year'), by('month')]).sum()
Out[56]:
a
2014 1 1.0
2 1.0
3 1.0
4 1.0
5 1.0
6 1.0
7 1.0
8 1.0
9 1.0
10 1.0
11 1.0
12 1.0
2015 1 1.0
More explicitly 更明确地
In [57]: df.groupby([df.index.year, df.index.month]).sum()
Out[57]:
a
2014 1 1.0
2 1.0
3 1.0
4 1.0
5 1.0
6 1.0
7 1.0
8 1.0
9 1.0
10 1.0
11 1.0
12 1.0
2015 1 1.0
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.