pandas python - 类型错误：无法排序的类型：str() > float()
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python - TypeError: unorderable types: str() > float()
提问by Thoram Mastero
i have a csv file and has v3 column but that column has some 'nan' rows. How can i except the rows.
我有一个 csv 文件并且有 v3 列，但该列有一些“nan”行。我怎么能除了行。
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')
Edit: 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)
编辑：V3 列有 A、C、B、A、C、D、、、A、S，就像那样，我想将其转换为 (1,2,3,1,2,4,,,1, 7)
回答by Rob
Mask the nan values by using ~isnull():
使用 ~isnull() 屏蔽 nan 值：
mask = ~dataset['v3'].isnull()
dataset['v3'][mask] = enc.fit_transform(dataset['v3'][mask])
Another way is to use the pandas.factorize function, which takes care of the nans automatically (assigns them -1):
另一种方法是使用 pandas.factorize 函数，它会自动处理 nans（为它们分配 -1）：
dataset['v3'] = dataset['v3'].factorize()[0]
