Python 删除表中的列
在转换并添加了几列之后,我创建了一个如下所示的数据帧 初始df-Python 删除表中的列,python,pandas,Python,Pandas,在转换并添加了几列之后,我创建了一个如下所示的数据帧 初始df- plan_benefits value plan_benefits_db value_db valid_flag 0 durable_medical_equipment 20 durable_medical_equipment 40 False 1
plan_benefits value plan_benefits_db value_db valid_flag
0 durable_medical_equipment 20 durable_medical_equipment 40 False
1 pcp 45 pcp 40 False
2 specialist 80 specialist 40 False
3 diagnostic 7540 diagnostic 40 False
4 imaging 300 imaging 40 False
5 generic 30 generic 40500 False
6 formulary_brand 110 formulary_brand 40500 False
7 non_preferred_generic 55110 non_preferred_generic 40500 False
8 emergency_room 350 emergency_room 40 False
9 inpatient_facility 20 inpatient_facility 40 False
10 medical_deductible_single 2000 medical_deductible_single 6000 False
11 medical_deductible_family 4000 medical_deductible_family 12000 False
12 maximum_out_of_pocket_limit_single 7550 maximum_out_of_pocket_limit_single 6650 False
13 maximum_out_of_pocket_limit_family 15100 maximum_out_of_pocket_limit_family 13300 False
最终df-
plan_benefits durable_medical_equipment pcp specialist diagnostic imaging generic formulary_brand non_preferred_generic emergency_room inpatient_facility medical_deductible_single medical_deductible_family maximum_out_of_pocket_limit_single maximum_out_of_pocket_limit_family plan_name pdf_name
valid_flag False False False False False False False False False False False False False False ABCBCBC adjnajdn.pdf
我进行的手术-
df_repo = df_repo[['plan_benefits', 'valid_flag']].set_index('plan_benefits').transpose()
df_repo['plan_name'] = 'ABCBCBC'
df_repo['pdf_name'] = 'adjnajdn.pdf'
# df_repo = df_repo.drop('plan_benefits', 1)
print(df_repo.to_string())
我需要删除第一列“计划福利”。使用drop()
时,我得到keyrerror:“['plan\u benefits']未在axis中找到”
我尝试过多种选择,如del df(计划福利),但都不起作用
在评论中的答案之后进行最终定稿-
durable_medical_equipment pcp specialist diagnostic imaging generic formulary_brand non_preferred_generic emergency_room inpatient_facility medical_deductible_single medical_deductible_family maximum_out_of_pocket_limit_single maximum_out_of_pocket_limit_family plan_name pdf_name
0 False False False False False False False False False False False False False False ABCBCBC adjnajdn.pdf
首先需要删除列名称并创建默认索引:
df = (df_repo[['plan_benefits', 'valid_flag']].set_index('plan_benefits')
.T.reset_index(drop=True))
df.columns.name = None
或:
最后添加index=False
:
顺便说一句,由于索引已删除,解决方案应简化:
df = df_repo[['plan_benefits', 'valid_flag']].set_index('plan_benefits').transpose()
df.to_excel('file.xlsx', index=False)
首先需要删除列名称并创建默认索引:
df = (df_repo[['plan_benefits', 'valid_flag']].set_index('plan_benefits')
.T.reset_index(drop=True))
df.columns.name = None
或:
最后添加index=False
:
顺便说一句,由于索引已删除,解决方案应简化:
df = df_repo[['plan_benefits', 'valid_flag']].set_index('plan_benefits').transpose()
df.to_excel('file.xlsx', index=False)
@Jezrael当我打印print(df_repo.index.name)时,我已经得到了
None.
和print(df_repo.columns.name)
?我得到了plan_福利
所以使用df_repo.columns.name=None
所以在打印(df_repo.index.name)时也使用df_repo=df_repo.reset_.index.name
@Jezrael我已经得到了None.
和打印(df\u repo.columns.name)
?我得到了计划福利
所以使用df\u repo.columns.name=None
所以也使用df\u repo=df\u repo.reset\u索引(drop=True)