加权平均Pandas

Question

我有一个包含林分id、树种、高度和体积的数据框：

import pandas as pd

df=pd.DataFrame.from_items([('STAND_ID',[1,1,2,3,3,3]),('Species',['Conifer','Broadleaves','Conifer','Broadleaves','Conifer','Conifer']),
                             ('Height',[20,19,13,24,25,18]),('Volume',[200,100,300,50,100,10])])

   STAND_ID      Species  Height  Volume
0         1      Conifer      20     200
1         1  Broadleaves      19     100
2         2      Conifer      13     300
3         3  Broadleaves      24      50
4         3      Conifer      25     100
5         3      Conifer      18      10

我想按展位id分组和取消堆叠，并计算体积加权平均高度，因此我尝试：

^{pr2}$

高度当然不是体积加权平均值。我怎样才能给它们称重？如图3和针叶树：

(25*100 + 18*10)/(100+10)=24.4

Answer 1

如果我理解正确，一种方法是使用apply执行groupby：

df
   STAND_ID      Species  Height  Volume
0         1      Conifer      20     200
1         1  Broadleaves      19     100
2         2      Conifer      13     300
3         3  Broadleaves      24      50
4         3      Conifer      25     100
5         3      Conifer      18      10

df.groupby(['STAND_ID','Species']).apply(lambda x: (x['Height'] * x['Volume'].div(x['Volume'].sum())).sum()).unstack()

Species   Broadleaves    Conifer
STAND_ID                        
1                19.0  20.000000
2                 NaN  13.000000
3                24.0  24.363636

Answer 2

如果lambda函数令人困惑，^{也可以与函数定义一起使用。（还有一个函数numpy.average来计算加权平均值）

import numpy as np
def weighted_average(group):
   weights = group['Volume']
   height = group['Height']   
   return np.average(height,weights=weights)

df.groupby(['STAND_ID','Species']).apply(func = weighted_average).unstack()