使用Pandas将列复制到文件时出现问题

Question

代码的目标只是在两列中执行OHE，并按照原始文件中的方式编写其余的列。但是Dur列，如图所示，当它被写入第二个文件并传递了比它应该传递的更多的内容时，不知何故是“bug”。我不想限制字段，因为原始文件太大，可能有行与更长和更短的字段，这可能会使以后的分析复杂化

Image of the problem

import pandas as pd
from sklearn.preprocessing import LabelEncoder,OneHotEncoder

def opendataset():
    file = pd.read_csv('originalfiletest.binetflow')
    return file

def writefile():
    df.to_csv('newfiletest.binetflow', columns=['Dur','Proto','State','TotBytes','average_packet_size','average_bits_psecond'], index=False)

def writebackupproto():
    df.to_csv('fieldprotobackup.binetflow', columns=['Proto2','Proto'], index=False)

def writebackupstate():
    df.to_csv('fieldstatebackup.binetflow', columns=['State2','State'], index=False)

df = opendataset()

df['State2'] = df['State']
df['Proto2'] = df['Proto']

le = LabelEncoder()
dfle = df
dfle.State = le.fit_transform(dfle.State)
X = dfle[['State']].values
Y = dfle[['Proto']].values
ohe = OneHotEncoder()
OnehotX = ohe.fit_transform(X).toarray()
OnehotY = ohe.fit_transform(Y).toarray()

dx = pd.DataFrame(data=OnehotX)
dy = pd.DataFrame(data=OnehotY)

dfle['State'] = (dx[dx.columns[0:]].apply(lambda x:''.join(x.dropna().astype(int).astype(str)), axis=1))
dfle['Proto'] = (dy[dy.columns[0:]].apply(lambda y:''.join(y.dropna().astype(int).astype(str)), axis=1))

writefile()
writebackupproto()
writebackupstate()

Answer 1

看起来唯一的错误是你的值没有被截断。您只需使用带有“截断lambda”的pandas.Series.apply方法即可获得预期结果

df.Dur = df.Dur.apply(lambda n: '%.6f' % n) 

一个可行的例子可能是截断pi

from math import pi
non_truncated = pd.Series(10*[pi])
non_truncated.apply(lambda n: '%.2f' % n)

你得到一个截断的序列

0    3.14
1    3.14
2    3.14
3    3.14
4    3.14
5    3.14
6    3.14
7    3.14
8    3.14
9    3.14
dtype: object