Groupby计算，以及pandas中的轴函数

我有一个如下所示的数据框

Sector    Plot    Year       Amount   Month
SE1       1       2017       10       Sep
SE1       1       2018       10       Oct
SE1       1       2019       10       Jun
SE1       1       2020       90       Feb
SE1       2       2018       50       Jan
SE1       2       2017       100      May
SE1       2       2018       30       Oct
SE2       2       2018       50       Mar
SE2       2       2019       100      Jan

从上面我想准备下面

Sector    Plot   Number_of_Times    Mean_Amount    Recent_Amount   Recent_year   All   
SE1       1      4                  30             50              2020          {'2018':50,  '2017':10, '2019':10, 2020:90}
SE1       2      3                  60             30              2018          {'2018':50, '2017':100, '2018':30}
SE2       2      2                  75             100             2019          {'2018':50, '2019':100}

与

df1

的命名聚合一起使用，然后通过将

Year

s与

Amount

转换为每个组创建字典，并最终合并：

g = df.groupby(['Sector','Plot'])
df1 = (g.agg(Number_of_Times=('Year','size'),
             Mean_Amount=('Amount','mean'),
             Recent_Amount=('Amount','last'),
             Recent_year=('Year','last')))

s = g['Year','Amount'].apply(lambda x: dict(x.values)).rename('All')

关于

zip

和

dict

的另一个想法：

s = g.apply(lambda x: dict(zip(x['Year'], x['Amount']))).rename('All')

---

df2 = df1.join(s).reset_index()
print (df2)
  Sector  Plot  Number_of_Times  Mean_Amount  Recent_Amount  Recent_year  \
0    SE1     1                4           30             90         2020   
1    SE1     2                3           60             30         2018   
2    SE2     2                2           75            100         2019   

                                        All  
0  {2017: 10, 2018: 10, 2019: 10, 2020: 90}  
1                     {2018: 30, 2017: 100}  
2                     {2018: 50, 2019: 100}