相关疑难解决方法(0)

有没有办法编写DataFrame.agg方法中使用的聚合函数,可以访问聚合的多个数据列？典型的用例是加权平均加权标准偏差函数.

我希望能够写出类似的东西

def wAvg(c, w):
    return ((c * w).sum() / w.sum())

df = DataFrame(....) # df has columns c and w, i want weighted average
                     # of c using w as weight.
df.aggregate ({"c": wAvg}) # and somehow tell it to use w column as weights ...

有没有办法回顾前一行,并计算一个新变量？所以只要前一行是相同的情况是什么(先前的更改) - (当前的更改),并将其归因于新列中的前一个'ChangeEvent'？

这是我的DataFrame

>>> df
  ChangeEvent StartEvent  case              change      open  
0    Homeless   Homeless     1 2014-03-08 00:00:00 2014-02-08  
1       other   Homeless     1 2014-04-08 00:00:00 2014-02-08     
2    Homeless   Homeless     1 2014-05-08 00:00:00 2014-02-08      
3        Jail   Homeless     1 2014-06-08 00:00:00 2014-02-08     
4        Jail       Jail     2 2014-06-08 00:00:00 2014-02-08   

添加列

Jail  Homeless case
 0    6        1
 0    30       1
 0    0        1

... 等等

这是df构建

import pandas as pd
import datetime as DT
d = {'case' : pd.Series([1,1,1,1,2]),
'open' : pd.Series([DT.datetime(2014, 3, 2), …