Python pandas 比较会引发 TypeError：无法将 dtyped [float64] 数组与 [bool] 类型的标量进行比较
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pandas comparison raises TypeError: cannot compare a dtyped [float64] array with a scalar of type [bool]
提问by anonuser0428
I have the following structure to my dataFrame:
我的数据帧具有以下结构：
Index: 1008 entries, Trial1.0 to Trial3.84
Data columns (total 5 columns):
CHUNK_NAME 1008 non-null values
LAMBDA 1008 non-null values
BETA 1008 non-null values
HIT_RATE 1008 non-null values
AVERAGE_RECIPROCAL_HITRATE 1008 non-null values
chunks=['300_321','322_343','344_365','366_387','388_408','366_408','344_408','322_408','300_408']
lam_beta=[(lambda1,beta1),(lambda1,beta2),(lambda1,beta3),...(lambda1,beta_n),(lambda2,beta1),(lambda2,beta2)...(lambda2,beta_n),........]
my_df.ix[my_df.CHUNK_NAME==chunks[0]&my_df.LAMBDA==lam_beta[0][0]]
I want to get the rows of the Dataframe for a particular chunk lets say chunks[0] and particular lambda value. So in this case the output should be all rows in the dataframe having CHUNK_NAME='300_321' and LAMBDA=lambda1. There would be n rows one for each beta value that would be returned. But instead I get the follwoing error. Any help in solving this problem would be appreciated.
我想获取特定块的 Dataframe 行，比如 chunks[0] 和特定的 lambda 值。所以在这种情况下，输出应该是数据帧中具有 CHUNK_NAME='300_321' 和 LAMBDA=lambda1 的所有行。对于将返回的每个 beta 值，将有 n 行。但相反，我得到了以下错误。任何解决此问题的帮助将不胜感激。
TypeError: cannot compare a dtyped [float64] array with a scalar of type [bool]
采纳答案by ecatmur
&has higher precedence than ==. Write:
&具有比 更高的优先级==。写：
my_df.ix[(my_df.CHUNK_NAME==chunks[0])&(my_df.LAMBDA==lam_beta[0][0])]
^ ^ ^ ^
