如何在 pandas 中将所有IP地址列表转换为十进制数字 [英] How to convert all IP address lists to decimal numbers in Pandas

问题描述

有大量的列表数据，如何将所有IP地址转换为熊猫中的十进制数字并与第二列的值合并

There is huge list data, how to convert all IP addresses to decimal numbers in pandas and merge with the value of the second column

   import pandas as pd
   filename = "/Users/sda/Desktop/file"
   pdd = pd.read_csv(filename,header=None,sep='|',error_bad_lines=False, warn_bad_lines=False,skiprows=[0],
              names=['Name','Code','Ipv', 'Ip','Range','Date', 'Category'])
   pd.options.display.max_columns = None
   k = pdd[pdd['Ipv'].str.contains("ipv4") & pdd['Ip'].str.contains('[0-9]')]
   print(k[['Ip','Range','Code']])

我的输出:

        Ip         Range    Code
     2.16.0.0      524288   EU
     200.109.100.0 1024     RU
     200.109.102.0 1024     RU

只需要获取具有相同国家代码和范围号的第一个IP地址的十进制值即可，仅与第二列的值合并

only need to get the decimal value of the first IP address with the same country code and range number.merge with the value of the second column only

       IP         range code
    3362612224    2028  RU

推荐答案

IIUC，考虑到输出的数据框名称为df，如下所示:

IIUC, Considering the dataframe name of the output is df, something like this:

import socket, struct

def ip2int(ip):
    """
    Convert an IP string to int
    """
    packedIP = socket.inet_aton(ip)
    return struct.unpack("!L", packedIP)[0]

df['ip_int'] = df.Ip.apply(ip2int)
df['range_sum']=df.groupby(['Code'])['Range'].transform('sum')
df[df.Code.duplicated(keep='last')]

               Ip  Range Code      ip_int  range_sum
 1  200.109.100.0   1024   RU  3362612224       2048

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