我有一个df,格式如下:
Priority Mined_Category server date_reported Count Zscore_Volume
1 - Critical Memory issue xxxxxx111 2018-07-11 1 nan
1 - Critical Memory issue xxxxxx111 2018-08-11 1 nan
1 - Critical Memory issue yyyyyy195 2018-07-06 1 1.71
1 - Critical Memory issue yyyyyy195 2018-07-08 1 1.71
2 - High Memory issue abcabcabcba1410 2018-08-21 1 nan
我的目标是当Priority
Mined_Category
和Server
groupby计数为1时,用100替换nan;当Priority
Mined_Category
和Server
groupby计数大于1时,用1000替换nan
我试过以下代码:
> df_aggegrate_Volume.loc[(df_aggegrate_Volume.groupby(["Priority","Mined_Category","server"]).count()>1)&(df_aggegrate_Volume['Zscore_Volume'].isnull()) ,"Zscore_Volume"]= -100
但我得到以下错误:
ValueError: operands could not be broadcast together with shapes (7410,) (3,)
需要^{} 返回
Series
,大小与原始df
相同,由聚合值填充:相关问题 更多 >
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