Rog*_*ite -5 python csv pandas
作为输入,我有一个.csv文件,例如:
user, withdraw, date
50D8BF0DA22D6C914777D8F59DAAB4D8, -125, 01-02-2015
674BCF0CD236621E5680073334A73C32, -5, 01-02-2015
E17E1691D35FB2FB675E3B787B8BEDF1, -845, 01-02-2015
50D8BF0DA22D6C914777D8F59DAAB4D8, -250, 01-02-2015
674BCF0CD236621E5680073334A73C32, -98, 01-02-2015
50D8BF0DA22D6C914777D8F59DAAB4D8, -17, 01-02-2015
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我想识别所有类似的“哈希”代码,并将其更改为诸如“ user1”,“ user2”,“ user3”等标签。
我一直在尝试这样做,但熊猫没有成功。知道我能做什么吗?
首先将CSV读入Pandas DF:
df = pd.read_csv('/path/to/file.csv', skipinitialspace=True)
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产量:
In [84]: df
Out[84]:
user withdraw date
0 50D8BF0DA22D6C914777D8F59DAAB4D8 -125 01-02-2015
1 674BCF0CD236621E5680073334A73C32 -5 01-02-2015
2 E17E1691D35FB2FB675E3B787B8BEDF1 -845 01-02-2015
3 50D8BF0DA22D6C914777D8F59DAAB4D8 -250 01-02-2015
4 674BCF0CD236621E5680073334A73C32 -98 01-02-2015
5 50D8BF0DA22D6C914777D8F59DAAB4D8 -17 01-02-2015
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现在我们可以分解user列:
In [85]: df['user'] = 'user' + pd.Series((pd.factorize(df.user)[0]+1).astype(str))
In [86]: df
Out[86]:
user withdraw date
0 user1 -125 01-02-2015
1 user2 -5 01-02-2015
2 user3 -845 01-02-2015
3 user1 -250 01-02-2015
4 user2 -98 01-02-2015
5 user1 -17 01-02-2015
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并将DF写回csv:
df.to_csv('/path/to/file_new.csv', index=False)
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