我有一个数据框
TIMESTAMP P_ACT_KW PERIODE_TARIF P_SOUSCR
2016-01-01 00:00:00 116 HC 250
2016-01-01 00:10:00 121 HC 250
2016-01-01 00:20:00 121 NaN 250
要使用此数据框,我必须根据以下条件填充NaN值(HC或HP):
If (hour extracted from TIMESTAMP is in {0,1,2, 3, 4, 5, 22, 23}
所以我用HC代替NaN, 否则由惠普。 我做了这个功能:
def prep_data(data):
data['PERIODE_TARIF']=np.where(data['PERIODE_TARIF']in (0, 1,2, 3, 4, 5, 22, 23),'HC','HP')
return data
但是我收到了这个错误:
ValueError Traceback (most recent call last)
<ipython-input-23-c1fb7e3d7b82> in <module>()
----> 1 prep_data(df_energy2)
<ipython-input-22-04bd325f91cd> in prep_data(data)
1 # Nettoyage des données
2 def prep_data(data):
----> 3 data['PERIODE_TARIF']=np.where(data['PERIODE_TARIF']in (0, 1),'HC','HP')
4 return data
C:\Users\Demonstrator\Anaconda3\lib\site-packages\pandas\core\generic.py
in __nonzero__(self)
890 raise ValueError("The truth value of a {0} is ambiguous. "
891 "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
--> 892 .format(self.__class__.__name__))
893
894 __bool__ = __nonzero__
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
我该如何解决这个问题?
答案 0 :(得分:2)
使用isin
来测试会员资格:
data['PERIODE_TARIF']=np.where(data['PERIODE_TARIF'].isin([0, 1,2, 3, 4, 5, 22, 23]),'HC','HP')
in
无法理解如何评估布尔值数组,因为如果数组中有多个True
,它就会变得不明确,因此错误