如何将分类数据放入垃圾箱

Question

我有以下分类数据：

['Self employed', 'Government Dependent',
 'Formally employed Private', 'Informally employed',
 'Formally employed Government', 'Farming and Fishing',
 'Remittance Dependent', 'Other Income',
 'Don't Know/Refuse to answer', 'No Income']

我如何将它们放入例如这样的垃圾箱中：

 ['Government Dependent','Formally employed Government','Formally 
  employed Private'] = 0

 ['Remittance Dependent', 'Informally employed','Self employed','Other Income'] = 1
 ['Dont Know/Refuse to answer', 'No Income','Farming and Fishing'] = 2

我已经知道将数值数据放入分类箱...可以相反吗？

TRAIN = pd.read_csv("Train_v2.csv")
TRAIN['job_type'].unique()
output:
array(['Self employed', 'Government Dependent',
       'Formally employed Private', 'Informally employed',
       'Formally employed Government', 'Farming and Fishing',
       'Remittance Dependent', 'Other Income',
       'Dont Know/Refuse to answer', 'No Income'], dtype=object)

Answer 1

首先创建字典，通过交换进行更改，最后使用Series.map：

Answer 2

如果不属于类别0或1或2，则可以执行numpy.select并将

m1 = TRAIN['job_type'].isin(['Government Dependent','Formally employed Government','Formally employed Private'])
m2 = TRAIN['job_type'].isin(['Remittance Dependent', 'Informally employed'])
m3 = TRAIN['job_type'].isin(["Don't Know/Refuse to answer", 'No Income'])
TRAIN['new'] = np.select([m1, m2, m3], [0, 1, 2], np.nan)

设为值。np.where np.nan上的更多资源：