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31 lines
1.1 KiB
Python
31 lines
1.1 KiB
Python
import pandas as pd
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def merge():
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# 读取三份csv文件
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df1 = pd.read_csv("../_dataset/TrafficLabelling_/Friday-WorkingHours-Morning.pcap_ISCX.csv")
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df2 = pd.read_csv("../_dataset/TrafficLabelling_/Friday-WorkingHours-Afternoon-PortScan.pcap_ISCX.csv")
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df3 = pd.read_csv("../_dataset/TrafficLabelling_/Friday-WorkingHours-Afternoon-DDos.pcap_ISCX.csv")
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# 将它们拼合成一个DataFrame
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df = pd.concat([df1, df2, df3])
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# 保存为新的csv文件
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df.to_csv("../_dataset/TrafficLabelling_/Friday-WorkingHours-merged.csv", index=False)
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def select():
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df = pd.read_csv('../_dataset/TrafficLabelling_/Friday-WorkingHours-merged.csv')
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df_ddos = df[df.iloc[:, -1] == 'DDoS']
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df_ddos.to_csv('../_dataset/TrafficLabelling_/Friday-WorkingHours-DDoS.csv', index=False)
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def search(query: str, row_name: str):
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df = pd.read_csv('../_dataset/TrafficLabelling_/Friday-WorkingHours-merged.csv')
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result = df[df[row_name].str.contains(query)]
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print(result.head())
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if __name__ == "__main__":
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# merge()
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# select()
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search("172.16.0.1-192.168.10.50-49533-80-6", "Flow ID")
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