首先需要引入字典特征提取类
from sklearn.feature_extraction import DictVectorizer
def dict_demo():
#字典特征提取
data=[{'city':'北京','temperature':100},{'city':'上海','temperature':60},{'city':'深圳','temperature':30}]
#1.实例化一个转换器类
transfer= DictVectorizer(sparse=False)#默认为sparse=True,即为稀疏矩阵
#2.调用fit_transform()
#转换成one-hot编码
# 类别特征比较多-》字典类型
# DictVectorizer
data_new=transfer.fit_transform(data)
print("data_new:\n",data_new)
print("特征值名字:",transfer.get_feature_names())
return None