使用python从嵌套字典中获取特定键的值

我正在遍历pandas dataframe中的行，从特定列打印出嵌套字典。我的嵌套字典如下所示：

{'dek': "<p>Don't forget to buy a card</p>",
 'links': {'edit': {'dev': '//patty-menshealth.feature.net/en/content/edit/76517422-96ad-4b5c-a24a-c080c58bce0c',
   'prod': '//patty-menshealth.prod.com/en/content/edit/76517422-96ad-4b5c-a24a-c080c58bce0c',
   'stage': '//patty-menshealth.stage.net/en/content/edit/76517422-96ad-4b5c-a24a-c080c58bce0c'},
  'frontend': {'dev': '//menshealth.feature.net/trending-news/a19521193/fathers-day-weekend-plans/',
   'prod': '//www.menshealth.com/trending-news/a19521193/fathers-day-weekend-plans/',
   'stage': '//menshealth.stage.net/trending-news/a19521193/fathers-day-weekend-plans/'}},
 'header': {'title_color': 1, 'title_layout': 1},
 'sponsor': {'program_type': 1, 'tracking_urls': []},
 'social_dek': "<p>Don't forget to buy a card</p>",
 'auto_social': 0,
 'index_title': "\u200bWeekend Guide: Treat Your Dad Right This Father's Day",
 'short_title': "Treat Your Dad Right This Father's Day",
 'social_title': "\u200bWeekend Guide: Treat Your Dad Right This Father's Day",
 'editors_notes': '<p>nid: 2801076<br>created_date: 2017-06-16 13:00:01<br>compass_feed_date: 2017-06-21 14:01:58<br>contract_id: 40</p>',
 'seo_meta_title': "Treat Your Dad Right This Father's Day\u200b | Men’s Health",
 'social_share_url': '/trending-news/a19521193/fathers-day-weekend-plans/',
 'seo_related_links': {},
 'editor_attribution': 'by',
 'hide_from_homepage': 1,
 'syndication_rights': 3,
 'seo_meta_description': "\u200bFrom gifts to food ideas, we've got your Father's Day covered. Just don't forget to buy him a card."}

如何获取特定键的值？我试图用

print（key[5]，value

包含要获取的键的索引，但它给了我一个错误：TypeError:“int”对象不可下标

---

如何获取值？

对于没有直接解决原始问题表示歉意，但可能值得使用

json\u normalize

将嵌套列“展平”

例如，如果示例数据名为

字典

：

from pandas.io.json import json_normalize

# Flatten the nested dict, resulting in a DataFrame with 1 row and 23 columns
this_df = json_normalize(dictionary)

# Inspect the resulting columns. Is this structure useful?
this_df.columns
Index(['dek', 'social_dek', 'auto_social', 'index_title', 'short_title',
       'social_title', 'editors_notes', 'seo_meta_title', 'social_share_url',
       'editor_attribution', 'hide_from_homepage', 'syndication_rights',
       'seo_meta_description', 'links.edit.dev', 'links.edit.prod',
       'links.edit.stage', 'links.frontend.dev', 'links.frontend.prod',
       'links.frontend.stage', 'header.title_color', 'header.title_layout',
       'sponsor.program_type', 'sponsor.tracking_urls'],
      dtype='object')

data={'dek'：“别忘了买一张卡
”，
‘links’：{'edit'：{'dev'：'//patty menshhealth.feature.net/en/content/edit/76517422-96ad-4b5c-a24a-c080c58bce0c’，
“prod”：“//patty menshhealth.prod.com/en/content/edit/76517422-96ad-4b5c-a24a-c080c58bce0c”，
“stage”：“//patty menshealth.stage.net/en/content/edit/76517422-96ad-4b5c-a24a-c080c58bce0c”，
‘frontend’：{‘dev’：‘//menshhealth.feature.net/trending news/a19521193/fathers day weekend plannis/’，
“prod”：“//www.menshhealth.com/trending news/a19521193/父亲节周末计划/”，
'stage'：'//menshhealth.stage.net/trending news/a19521193/fathers day weekend plans/'}，
'header'：{'title\u color'：1，'title\u layout'：1}，
“发起人”：{“程序类型”：1，“跟踪URL”：[]}，
“社交网站”：“别忘了买张卡”
”，
“自动社交”：0，
“索引标题”：“\u200b周末指南：在父亲节正确对待你的父亲”，
“在父亲节好好对待你的父亲”，
“社交标题”：“\u200b周末指南：在父亲节正确对待你的父亲”，
“编辑笔记”：“nid:2801076
创建日期：2017-06-16 13:00:01
指南针订阅日期：2017-06-21 14:01:58
合同id:40
”，
‘seo_meta_title’：“在父亲节好好对待你的父亲\u200b |男人的健康”，
“社交分享网址”：“/趋势新闻/a19521193/父亲节周末计划/”，
“搜索引擎优化相关链接”：{}，
“编者署名”：“作者”，
“从主页隐藏”：1，
“银团权利”：3，
‘seo_meta_description’：“\u200b从礼物到食物创意，我们已经涵盖了你父亲节。只是别忘了给他买张贺卡。”}
def findValByKey（键：str，数据：dict，级别=0）：
对于data.keys（）中的i：
打印（“{}{}”。格式（级别*'-'，i））
如果i==键：
打印（'---已找到--'）
返回数据[键]
elif isinstance（数据[i]，目录）：
res=findValByKey（键，数据[i]，级别+1）
如果有的话：
返回res
打印（findValByKey（“标题颜色”，数据））

from pandas.io.json import json_normalize

# Flatten the nested dict, resulting in a DataFrame with 1 row and 23 columns
this_df = json_normalize(dictionary)

# Inspect the resulting columns. Is this structure useful?
this_df.columns
Index(['dek', 'social_dek', 'auto_social', 'index_title', 'short_title',
       'social_title', 'editors_notes', 'seo_meta_title', 'social_share_url',
       'editor_attribution', 'hide_from_homepage', 'syndication_rights',
       'seo_meta_description', 'links.edit.dev', 'links.edit.prod',
       'links.edit.stage', 'links.frontend.dev', 'links.frontend.prod',
       'links.frontend.stage', 'header.title_color', 'header.title_layout',
       'sponsor.program_type', 'sponsor.tracking_urls'],
      dtype='object')

data={'dek': "<p>Don't forget to buy a card</p>",
'links': {'edit': {'dev': '//patty-menshealth.feature.net/en/content/edit/76517422-96ad-4b5c-a24a-c080c58bce0c',
'prod': '//patty-menshealth.prod.com/en/content/edit/76517422-96ad-4b5c-a24a-c080c58bce0c',
'stage': '//patty-menshealth.stage.net/en/content/edit/76517422-96ad-4b5c-a24a-c080c58bce0c'},
'frontend': {'dev': '//menshealth.feature.net/trending-news/a19521193/fathers-day-weekend-plans/',
'prod': '//www.menshealth.com/trending-news/a19521193/fathers-day-weekend-plans/',
'stage': '//menshealth.stage.net/trending-news/a19521193/fathers-day-weekend-plans/'}},
'header': {'title_color': 1, 'title_layout': 1},
'sponsor': {'program_type': 1, 'tracking_urls': []},
'social_dek': "<p>Don't forget to buy a card</p>",
'auto_social': 0,
'index_title': "\u200bWeekend Guide: Treat Your Dad Right This Father's Day",
'short_title': "Treat Your Dad Right This Father's Day",
'social_title': "\u200bWeekend Guide: Treat Your Dad Right This Father's Day",
'editors_notes': '<p>nid: 2801076<br>created_date: 2017-06-16 13:00:01<br>compass_feed_date: 2017-06-21 14:01:58<br>contract_id: 40</p>',
'seo_meta_title': "Treat Your Dad Right This Father's Day\u200b | Men’s Health",
'social_share_url': '/trending-news/a19521193/fathers-day-weekend-plans/',
'seo_related_links': {},
'editor_attribution': 'by',
'hide_from_homepage': 1,
'syndication_rights': 3,
'seo_meta_description': "\u200bFrom gifts to food ideas, we've got your Father's Day covered. Just don't forget to buy him a card."}

def findValByKey(key:str, data:dict, level=0):
    for i in data.keys():
        print("{} {}".format(level*'-', i))
        if i==key:
            print('---found---')
            return data[key]
        elif isinstance(data[i], dict):
            res = findValByKey(key, data[i], level+1)
            if res:
                return res


print(findValByKey('title_color', data))