global_station_temperature=\
[{'year':2017,'month':'Jan','temperature':113},
{'year':2017,'month':'Feb','temperature':141},
{'year':2017,'month':'Mar','temperature':137},
{'year':2017,'month':'Apr','temperature':115},
{'year':2017,'month':'May','temperature':122},
{'year':2017,'month':'Jun','temperature':76},
{'year':2017,'month':'Jul','temperature':108},
{'year':2017,'month':'Aug','temperature':110},
{'year':2017,'month':'Sep','temperature':96},
{'year':2017,'month':'Oct','temperature':115},
{'year':2017,'month':'Nov','temperature':105},
{'year':2017,'month':'Dec','temperature':115},
{'year':2018,'month':'Jan','temperature':103},
{'year':2018,'month':'Feb','temperature':114},
{'year':2018,'month':'Mar','temperature':121},
{'year':2018,'month':'Apr','temperature':120},
{'year':2018,'month':'May','temperature':100},
{'year':2018,'month':'Jun','temperature':86},
{'year':2018,'month':'Jul','temperature':106},
{'year':2018,'month':'Aug','temperature':90},
{'year':2018,'month':'Sep','temperature':89},
{'year':2018,'month':'Oct','temperature':111},
{'year':2018,'month':'Nov','temperature':97},
{'year':2018,'month':'Dec','temperature':121}]
from sklearn.feature_extraction import DictVectorizer
DV=DictVectorizer(sparse=False)
temp_features=DV.fit_transform(global_station_temperature)
temp_features=temp_features.astype('int16')
print(DV.get_feature_names_out()[:5])
print(DV.get_feature_names_out()[5:10])
print(DV.get_feature_names_out()[10:])