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问题描述

我有一个csv文件并具有v3列,但该列具有一些"nan"行.除了行,我该怎么办.

i have a csv file and has v3 column but that column has some 'nan' rows.How can i except the rows.

 dataset = pd.read_csv('mypath') 

    enc = LabelEncoder()
    enc.fit(dataset['v3'])
    print('fitting')
    dataset['v3'] = enc.transform(dataset['v3'])
    print('transforming')
    print(dataset['v3'])
    print('end')

V3列具有A,C,B,A,C,D 、、、 A,S,就像这样,我想将其转换为(1,2,3,1,2,4 ,, ,1,7)

V3 columns has A,C,B,A,C,D,,,A,S, like that,and i want to convert it to (1,2,3,1,2,4,,,1,7)

推荐答案

使用〜isnull()屏蔽nan值:

Mask the nan values by using ~isnull():

mask = ~dataset['v3'].isnull()
dataset['v3'][mask] = enc.fit_transform(dataset['v3'][mask])

另一种方法是使用pandas.factorize函数,该函数自动处理nan(将其分配为-1):

Another way is to use the pandas.factorize function, which takes care of the nans automatically (assigns them -1):

dataset['v3'] = dataset['v3'].factorize()[0]

这篇关于python-TypeError:无法排序的类型:str()>漂浮()的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!

10-19 16:00