如何使用 pandas 对 csv 文件中的相同数字求和

How to sum same number in a csv file using pandas

我有一个 csv 文件,其中包含日期、计数和服务列。有很多日期、计数和服务列,但这是我将在下面编写的示例。

Number  Count   Service       Number    Count   service
0        13   NO SERVICE        0        10 
1        14   tcpmux            1        10 
2         9   compressnet       2        14 

所以我想要这样的答案:

Number   Total Count    Service
0            23         NO SERVICE
1            24         tcpmux
2            23         compressnet

如何执行 pandas

中的代码
import pandas as pd
df =pd.read_csv ("/Users/mani/Desktop/monthly report/geoip/2017-20dstipsum12.csv")
hasil =  df.groupby(['NUMBER']).sum()
hasil.to_csv('gotttt.txt', sep='\t', encoding='utf-8')

如果第 Number 列在所有数据中都相同:

#sum all column Count
df['Total Count'] = df['Count'].sum(axis=1)
#select first and third column and join Total Count column
df = df.iloc[:, [0,2]].join(df['Total Count'])
print (df)
   Number  Total Count   Total Service
0       0           23      NO SERVICE
1       1           24          tcpmux  
2       2           23     compressnet  

在较新版本的 pandas 中,read_csv 中的列名已被删除,因此 select 列需要 filter

print (df)
   Number  Count      Service  Number.1  Count.1 Service.1
0       0     13   NO SERVICE         0       10          
1       1     14       tcpmux         1       10          
2       2      9  compressnet         2       14 

df['Total Count'] = df.filter(like='Count').sum(axis=1)

df = df[['Number','Total Count','Service']]
print (df)
   Number  Total Count   Total Service
0       0           23      NO SERVICE  
1       1           24          tcpmux 
2       2           23     compressnet