用同一类别编码多列的标签

Question

import pandas as pd
from sklearn.preprocessing import LabelEncoder

df = pd.DataFrame(data=[["France", "Italy", "Belgium"], ["Italy", "France", "Belgium"]], columns=["a", "b", "c"])
df = df.apply(LabelEncoder().fit_transform)
print(df)

   a  b  c
0  0  1  0
1  1  0  0

我的目标是通过传入我想要共享分类值的列，使其输出如下所示：

   a  b  c
0  0  1  2
1  1  0  2

Answer 1

传递axis=1以对每一行调用labelencoder().fit_transform一次。（默认情况下，df.apply(func)为每列调用func一次）。

import pandas as pd
from sklearn.preprocessing import LabelEncoder

df = pd.DataFrame(data=[["France", "Italy", "Belgium"], 
                        ["Italy", "France", "Belgium"]], columns=["a", "b", "c"])

encoder = LabelEncoder()

df = df.apply(encoder.fit_transform, axis=1)
print(df)

产量

   a  b  c
0  1  2  0
1  2  1  0

或者，您可以使用make the data ofcategorydtype，并使用类别代码作为标签：

import pandas as pd

df = pd.DataFrame(data=[["France", "Italy", "Belgium"], 
                        ["Italy", "France", "Belgium"]], columns=["a", "b", "c"])

stacked = df.stack().astype('category')
result = stacked.cat.codes.unstack()
print(result)

   a  b  c
0  1  2  0
1  2  1  0