如果条件满足，如何应用熊猫并将条件满足时写入新列？

Question

我要在csv文件上应用这两个条件

1.（Fwd数据包的总长度$ <= 0.00003225和Fwd数据包的总长度<= 0.000043 AND Fwd数据包的最大长度> 0.00021549999999999998）

2.（转发数据包最大长度<= 0.00021549999999999998）

如果这些条件成立，我想在“活动”列中写入攻击，然后将整个文件写入带有活动的新csv中

code

import pandas as pd
import numpy as np
from sklearn.feature_selection import SelectKBest
from sklearn.feature_selection import chi2
import codecs
import csv

main_labels=["Total Length of Fwd Packets","Fwd Packet Length Max","Flow Bytes/s","Label","Activity"]


df = pd.read_csv('portscanfeatures.csv',usecols=main_labels)

attack_or_not=[]

for i in df["Fwd Packet Length Max"]:#it changes the normal label to "1" and 

the attack tag to "0" for use in the machine learning algorithm

if i <= 0.00021549999999999998:
    attack_or_not.append(1)
else:
    attack_or_not.append(0)

Answer 1

这有效。只需列出条件，然后使用numpy.where放置所需的值即可。

import numpy as np

conditions = ((df['Total Length of Fwd Packets'] <= 0.00003225) & (df['Total Length of Fwd Packets'] <= 0.000043) & (df['Fwd Packet Length Max'] > 0.00021549999999999998) & (df['Fwd Packet Length Max'] <=0.00021549999999999998))

df['attack'] = np.where(conditions, 'Attack', "Don't")

#or if you want 1, 0 directly

df['attack'] = np.where(conditions, 1, 0)