如何根据另一列中的单元格值有条件填充熊猫列

Question

我有一个大约10000行的数据框，并希望根据某些条件填充多列。

如果操作系统包含“ Windows Server”，则平台要使用服务器或包含（“ Windows 7 | Windows 10”），而不是平台要使用“ Workstation”

我尝试过的代码：

conditions = [
    (dfADTM['Operating System'].str.contains('Windows Server')),
    (dfADTM['Operating System'].str.contains('Windows 10|Windows 7|Windows XP')),
    (dfADTM['Operating System'].str.contains('Cisco|SLES|OnTap|unknown'))]
choices = ['Server', 'Workstation', 'Network Appliance']
dfADTM['Platform AD'] = np.select(conditions, choices, default='Check')
print(dfADTM.head())

我面临的错误：

[Running] python -u "c:\Users\Abhinav Kumar\Desktop\weekly\code.py"
Traceback (most recent call last):
  File "c:\Users\Abhinav Kumar\Desktop\weekly\code.py", line 36, in <module>
    dfADTM['Platform AD'] = np.select(conditions, choices, default='Check')
  File "C:\ProgramData\Anaconda3\lib\site-packages\numpy\lib\function_base.py", line 715, in select
    'invalid entry {} in condlist: should be boolean ndarray'.format(i))
ValueError: invalid entry 0 in condlist: should be boolean ndarray

[Done] exited with code=1 in 7.725 seconds

预期的结果数据帧为：

Answer 1

这不是一种有效的方法，但是可以完成工作

df.index

for i in range(0,len(df)):
    if df['OS'][i].split(" ")[1]=='Server':
      df.set_value(i, 'Platform', 'Server')
    if df['OS'][i].split(" ")[1]=='7' or df['OS'][i].split(" ")[1]=='10':
      df.set_value(i, 'Platform', 'Workstation')

如果需要，您可以删除索引或将其重置

Answer 2

您可以尝试以下操作： `

import numpy as np
import pandas as pd
df['Platform']=np.nan #create an empty column in the dataframe
for i in range(len(df)):
        a=df['Operating System'][i]
        if ('Windows 10' or 'Windows 7' or 'Windows XP')  in a:
            df['Platform'][i]='Workstation'
        elif ('Cisco' or 'SLES' or 'OnTap' or 'unknown') in a:
            df['Platform'][i]='Network Appliance'
        elif ('Windows Server') in a:
            df['Platform'][i]='Server'
        else:
            df['Platform'][i]='Not mentioned' #For the values which do no fall into any category
`