pandas 比较引发TypeError:无法将dtyped [float64]数组与类型为[bool]的标量进行比较 [英] pandas comparison raises TypeError: cannot compare a dtyped [float64] array with a scalar of type [bool]

问题描述

我的dataFrame具有以下结构:

I have the following structure to my dataFrame:

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]]

我想获取特定块的数据帧的行，可以说chunks [0]和特定的lambda值.因此，在这种情况下，输出应为数据帧中具有CHUNK_NAME ='300_321'和LAMBDA = lambda1的所有行.每个返回的Beta值将有n行.但是相反，我遇到了以下错误.解决该问题的任何帮助将不胜感激.

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.

TypeError: cannot compare a dtyped [float64] array with a scalar of type [bool]

推荐答案

&的优先级高于==.写:

my_df.ix[(my_df.CHUNK_NAME==chunks[0])&(my_df.LAMBDA==lam_beta[0][0])]
         ^                           ^ ^                            ^

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