Pandas 将分类列转换为单个虚拟变量列

假设我有以下数据帧：

   Survived  Pclass     Sex   Age     Fare
0         0       3    male  22.0   7.2500
1         1       1  female  38.0  71.2833
2         1       3  female  26.0   7.9250
3         1       1  female  35.0  53.1000
4         0       3    male  35.0   8.0500

  Category                                            Message
0      ham  Go until jurong point, crazy.. Available only ...
1      ham                      Ok lar... Joking wif u oni...
2     spam  Free entry in 2 a wkly comp to win FA Cup final...
3      ham  U dun say so early hor... U c already then say...
4      ham  Nah I don't think he goes to usf, he lives aro...

我使用get_dummies（）函数来创建虚拟变量。代码和输出如下所示：

one_hot = pd.get_dummies(dataset, columns = ['Category'])

这将返回：

   Survived  Pclass  Age     Fare  Sex_female  Sex_male
0         0       3   22   7.2500           0         1
1         1       1   38  71.2833           1         0
2         1       3   26   7.9250           1         0
3         1       1   35  53.1000           1         0
4         0       3   35   8.0500           0         1

我想要的是一个单独的Sex列，其值为0或1，而不是2列

有趣的是，当我在不同的数据帧上使用get_dummies（）时，它的工作方式与我所希望的一样。
对于以下数据帧：

   Survived  Pclass     Sex   Age     Fare
0         0       3    male  22.0   7.2500
1         1       1  female  38.0  71.2833
2         1       3  female  26.0   7.9250
3         1       1  female  35.0  53.1000
4         0       3    male  35.0   8.0500

  Category                                            Message
0      ham  Go until jurong point, crazy.. Available only ...
1      ham                      Ok lar... Joking wif u oni...
2     spam  Free entry in 2 a wkly comp to win FA Cup final...
3      ham  U dun say so early hor... U c already then say...
4      ham  Nah I don't think he goes to usf, he lives aro...

使用代码：

one_hot = pd.get_dummies(dataset, columns = ['Category'])

它返回：

                                             Message  ...  Category_spam
0  Go until jurong point, crazy.. Available only ...  ...              0
1                      Ok lar... Joking wif u oni...  ...              0
2  Free entry in 2 a wkly comp to win FA Cup fina...  ...              1
3  U dun say so early hor... U c already then say...  ...              0
4  Nah I don't think he goes to usf, he lives aro...  ...              0

为什么get_dummies（）在这两个数据帧上的工作方式不同

如何确保每次都获得第二个输出

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以下是您可以使用的多种方法：

from sklearn.preprocessing import LabelEncoder

lbl=LabelEncoder()
df['Sex_encoded'] = lbl.fit_transform(df['Sex'])

# using only pandas
df['Sex_encoded'] = df['Sex'].map({'male': 0, 'female': 1})

   Survived  Pclass     Sex   Age     Fare  Sex_encoded
0         0       3    male  22.0   7.2500            0
1         1       1  female  38.0  71.2833            1
2         1       3  female  26.0   7.9250            1
3         1       1  female  35.0  53.1000            1
4         0       3    male  35.0   8.0500            0

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为什么get_假人在问题中提到的2个不同数据帧上的工作方式不同？@user41855可能检查数据帧中变量的类型，可能不同。