Question

我的表格如下：

import pandas as pd
import numpy as np

#simple table
fazenda = [6010,6010,6010,6010]
quadra = [1,1,2,2]
talhao = [1,2,3,4]
arTotal = [32.12,33.13,34.14,35.15]
arCarr = [i/2 for i in arTotal]
arProd = [i/2 for i in arTotal]
varCan = ['RB1','RB2','RB3','RB4']
data = list(zip(fazenda,quadra,talhao,arTotal,arCarr,arProd,varCan))

#Pandas DataFrame
df = pd.DataFrame(data=data,columns=['Fazenda','Quadra','Talhao','ArTotal','ArCarr','ArProd','Variedade'])

#Pivot Table
table = pd.pivot_table(df, values=['ArTotal','ArCarr','ArProd'],index=['Quadra','Talhao'], fill_value=0)

print(table)

导致：

               ArCarr  ArProd  ArTotal
Quadra Talhao                         
1      1       16.060  16.060    32.12
       2       16.565  16.565    33.13
2      3       17.070  17.070    34.14
       4       17.575  17.575    35.15

我需要两个附加步骤：

为'ArTotal'添加小计和总计，'ArCarr'e'ArProd'字段
将'Variedade'字段添加到表格

我尝试添加列但结果不正确。关于Total和Grand Total的一些链接，我没有得到满意的结果。

我很难理解大熊猫，我向更有经验的同事寻求帮助。

Answer 1

首先获取pivot权利。

In [404]: values = ['ArTotal','ArCarr','ArProd']

In [405]: table = pd.pivot_table(df, values=values, index=['Quadra','Talhao','Variedade'], 
                                 fill_value=0).reset_index(level=-1)

获得总计

In [406]: Gt = table[values].sum()

获取Quadra级别总计

In [407]: St = table.sum(level='Quadra')

使用append重塑table

In [408]: (table.append(
                 St.assign(Talhao='Total').set_index('Talhao', append=True)
                ).sort_index()
                .append(pd.DataFrame([Gt.values], columns=Gt.index,
                                     index=pd.MultiIndex.from_tuples([('Grand Total', '')],
                                     names=['Quadra', 'Talhao']))
                ).fillna(''))
Out[408]:
                    ArCarr  ArProd  ArTotal Variedade
Quadra      Talhao
1           1       16.060  16.060    32.12       RB1
            2       16.565  16.565    33.13       RB2
            Total   32.625  32.625    65.25
2           3       17.070  17.070    34.14       RB3
            4       17.575  17.575    35.15       RB4
            Total   34.645  34.645    69.29
Grand Total         67.270  67.270   134.54

详细

In [409]: table
Out[409]:
              Variedade  ArCarr  ArProd  ArTotal
Quadra Talhao
1      1            RB1  16.060  16.060    32.12
       2            RB2  16.565  16.565    33.13
2      3            RB3  17.070  17.070    34.14
       4            RB4  17.575  17.575    35.15

In [410]: Gt
Out[410]:
ArTotal    134.54
ArCarr      67.27
ArProd      67.27
dtype: float64

In [411]: St
Out[411]:
        ArCarr  ArProd  ArTotal
Quadra
1       32.625  32.625    65.25
2       34.645  34.645    69.29

Answer 2

我认为John的解决方案胜过我，但根据您当前的输出，您无法通过数据透视表执行此操作，您可以使用列表理解分组数据进行一系列步骤，然后附加总和来执行此操作，即

cols = ['Fazenda','Variedade','Quadra','Talhao']
ndf = pd.concat([i.append(i.drop(cols,1).sum(),1) for _,i in df.groupby('Quadra')])

ndf['Talhao'] = ndf[['Talhao']].fillna('Total')
ndf['Quadra'] = ndf['Quadra'].ffill()

new = ndf.set_index(['Quadra','Talhao']).drop(['Fazenda'],1)

new = new.append(pd.DataFrame(df.sum()).T.drop(cols,1).set_index(pd.MultiIndex.from_tuples([('Grand Total', '')]))).fillna('')

输出：

                    ArCarr  ArProd  ArTotal Variedade
Quadra      Talhao                                   
1.0         1.0     16.060  16.060    32.12       RB1
            2.0     16.565  16.565    33.13       RB2
            Total   32.625  32.625    65.25          
2.0         3.0     17.070  17.070    34.14       RB3
            4.0     17.575  17.575    35.15       RB4
            Total   34.645  34.645    69.29          
Grand Total         67.270  67.270   134.54

使用pandas将数据列添加到数据透视表

2 个答案: