Python 获取多列的总和和平均值，并将结果追加为一行

我读取了一个csv文件，我想创建一个新行，其中包含一些结果，3列为

sum（）

，其余列为

mean（）

。问题是我的输出是这样的：

Total                   1596260396              
Total2                      30453841            
Tota3                           3.024863813     
Total4                              19742.04    
Total5                                  0.733696498

我正在寻找这个：

Total 1596260396 30453841 3.024863813 19742.04 0.733696498

我的代码：

# encoding=utf8  
from io import StringIO
import pandas as pd
import os
from pandas import ExcelWriter
import sys
reload(sys)
sys.setdefaultencoding('utf-8')

df1 = pd.read_csv("este_mes.csv", sep=',')
df1.loc['Total'] = pd.Series(df1['Subastas'].sum(), index = ['Subastas'])
df1.loc['Total2'] = pd.Series(df1['Impresiones_exchange'].sum(), index = ['Impresiones_exchange'])
df1.loc['Tota3'] = pd.Series(df1['Fill_rate'].mean(), index = ['Fill_rate'])
df1.loc['Total4'] = pd.Series(df1['Importe_a_pagar_a_medio'].sum(), index = ['Importe_a_pagar_a_medio'])
df1.loc['Total5'] = pd.Series(df1['ECPM_medio'].mean(), index = ['ECPM_medio'])

我的csv的某些行：

Cliente,Fecha,Status,cl_fecha,Subastas,Impresiones_exchange,Fill_rate,Importe_a_pagar_a_medio,ECPM_medio
jjj,01/01/2017,Alerta Fillrate - Revenue - Imp Vendidas,jjj_01/01/2017,2277331,25843,1.13,10.36,0.4
jjj,02/01/2017,Alerta Fillrate -- Incremento Revenue - Imp Vendidas - Subastadas,jjj_02/01/2017,6747816,42957,0.64,17.9,0.42
jjj,03/01/2017,Alerta Fillrate - Revenue - Imp Vendidas:  aumento eCPM-- CRITICO,jjj_03/01/2017,6397915,27926,0.44,13.1,0.47
jjj,04/01/2017,Estable: descenso Revenue e Imp Vendidas,jjj_04/01/2017,5764124,22940,0.4,11.14,0.49
jjj,05/01/2017,Estable,jjj_05/01/2017,5635852,23924,0.42,11.24,0.47

我想要的输出：

Cliente,Fecha,Status,cl_fecha,Subastas,Impresiones_exchange,Fill_rate,Importe_a_pagar_a_medio,ECPM_medio
    jjj,01/01/2017,Alerta Fillrate - Revenue - Imp Vendidas,jjj_01/01/2017,2277331,25843,1.13,10.36,0.4
    jjj,02/01/2017,Alerta Fillrate -- Incremento Revenue - Imp Vendidas - Subastadas,jjj_02/01/2017,6747816,42957,0.64,17.9,0.42
    jjj,03/01/2017,Alerta Fillrate - Revenue - Imp Vendidas:  aumento eCPM-- CRITICO,jjj_03/01/2017,6397915,27926,0.44,13.1,0.47
    jjj,04/01/2017,Estable: descenso Revenue e Imp Vendidas,jjj_04/01/2017,5764124,22940,0.4,11.14,0.49
    jjj,05/01/2017,Estable,jjj_05/01/2017,5635852,23924,0.42,11.24,0.47

    Total 1596260396 30453841 3.024863813 19742.04 0.733696498

---

定义求和列和平均列-

s = ['Subastas', 'Impresiones_exchange', 'Importe_a_pagar_a_medio']
m = ['Fill_rate', 'ECPM_medio']

接下来，切片并计算-

i = df1[s].sum()
i

Subastas                   26823038.00
Impresiones_exchange         143590.00
Importe_a_pagar_a_medio          63.74
dtype: float64

连接两个-

v = pd.concat([i, j])
v

Subastas                   2.682304e+07
Impresiones_exchange       1.435900e+05
Importe_a_pagar_a_medio    6.374000e+01
Fill_rate                  6.060000e-01
ECPM_medio                 4.500000e-01
dtype: float64

并重塑您的输出-

df = pd.DataFrame(v.values[:, None].T, index=['Total'], columns=v.index)
df

         Subastas  Impresiones_exchange  Importe_a_pagar_a_medio  Fill_rate  \
Total  26823038.0              143590.0                    63.74      0.606   

       ECPM_medio  
Total        0.45 

要写入现有CSV，请使用

a

ppend模式-

df.to_csv('file.csv', mode='a')

---

能给我5-10行你的输入吗？那会有帮助的。我刚刚添加了@cᴏʟᴅᴘᴇᴇᴅ你们能在记事本或升华文本中打开它并和分隔符一起复制吗？完成！现在好了吗@cᴏʟᴅᴘᴇᴇᴅ好的，那么你想把这个输出放到哪里？

df.to_csv('file.csv', mode='a')