AttributeError:“Series”对象没有属性“value”

Question

我想得到一份电话号码的清单

这是密码

response='108'
group="MAMA"
optout='False'

phone_numbers = merged_df.loc[(merged_df['Facility Code'] ==facility_number) & (merged_df['group'] == group) & (merged_df['Optedout'] == optout)]['phone'].values
    print(phone_numbers)

我的数据框看起来是这样的

phone       group   County  PNC/ANC Facility Name   Optedout    Facility Code
25470000000 MAMA    Orange  PNC     Main Centre       FALSE      112
25470000000 MAMA    Orange  PNC     Main Centre       FALSE      112
25470000010 MAMA    Orange  PNC     Centre            FALSE      108
25470000020 MAMA    Orange  PNC     Centre            FALSE      108
25470000000 MAMA    Orange  PNC     Main Centre       FALSE      112

这就是我得到的错误

AttributeError: 'Series' object has no attribute 'value'

期望输出

[25470000010,25470000020]

我似乎不知道我做错了什么。请帮我修一下

Answer 1

@Serge Ballesta的评论是最有可能的原因

您共享的代码中存在拼写错误。检查是否调用了value而不是values

以下代码按预期工作：

import pandas as pd

data = {'phone': [25470000000, 25470000000, 25470000010, 25470000020, 25470000000], 'group': ['MAMA', 'MAMA', 'MAMA', 'MAMA', 'MAMA'], 'County': ['Orange', 'Orange', 'Orange', 'Orange', 'Orange'], 'PNC/ANC': ['PNC', 'PNC', 'PNC', 'PNC', 'PNC'], 'Facility Name': ['Main Centre', 'Main Centre', 'Centre', 'Centre', 'Main Centre'], 'Optedout': ['FALSE', 'FALSE', 'FALSE', 'FALSE', 'FALSE'], 'Facility Code': [112, 112, 108, 108, 112]}

merged_df = pd.DataFrame.from_dict(data)

facility_number = 108
group = 'MAMA'
optout = 'FALSE'

phone_numbers = merged_df.loc[(merged_df['Facility Code'] ==facility_number) & (merged_df['group'] == group) & (merged_df['Optedout'] == optout)]['phone'].values

print(phone_numbers)

输出：

[25470000010 25470000020]

通过删除.values，输出是一个数据帧：

2    25470000010
3    25470000020
Name: phone, dtype: int64

Answer 2

您需要删除.values：

phone_numbers = merged_df.loc[(merged_df['Facility Code'] ==facility_number) & (merged_df['group'] == group) & (merged_df['Optedout'] == optout)]['phone']