2023年2月10日 04:39:09go评论103阅读模式

英文:

Python converting a list in a nested dictionary into a Pandas Dataframe

问题

我有以下的字典

test = {'data': [
  {'actions': [
    {'action_type': 'link_click', 'value': '16'},
    {'action_type': 'post_engagement', 'value': '16'},
    {'action_type': 'page_engagement', 'value': '16'}],
   'spend': '13.59',
   'date_start': '2023-02-07',
   'date_stop': '2023-02-07'},
  {'actions': [
    {'action_type': 'comment', 'value': '5'},
    {'action_type': 'onsite_conversion.post_save', 'value': '1'},
    {'action_type': 'link_click', 'value': '465'},
    {'action_type': 'post', 'value': '1'},
    {'action_type': 'post_reaction', 'value': '20'},
    {'action_type': 'video_view', 'value': '4462'},
    {'action_type': 'post_engagement', 'value': '4954'},
    {'action_type': 'page_engagement', 'value': '4954'}],
   'spend': '214.71',
   'date_start': '2023-02-07',
   'date_stop': '2023-02-07'}]}

我尝试将它转换为每个 action_type 后面的元素作为 pandas DataFrame 列，值作为行，类似如下：

link_click post_engagement page_engagement   spend comment onsite_conversion ...
        16              16              16   13.59     N/A               N/A
       465            4954            4954  214.71       5                 1

我明白第一个列表没有 comment、post 等，行会是 N/A。如何管理这种复杂的数据结构？

英文:

I have the following dictionary

test = {&#39;data&#39;: [
  {&#39;actions&#39;: [
    {&#39;action_type&#39;: &#39;link_click&#39;, &#39;value&#39;: &#39;16&#39;},
    {&#39;action_type&#39;: &#39;post_engagement&#39;, &#39;value&#39;: &#39;16&#39;},
    {&#39;action_type&#39;: &#39;page_engagement&#39;, &#39;value&#39;: &#39;16&#39;}],
   &#39;spend&#39;: &#39;13.59&#39;,
   &#39;date_start&#39;: &#39;2023-02-07&#39;,
   &#39;date_stop&#39;: &#39;2023-02-07&#39;},
  {&#39;actions&#39;: [
    {&#39;action_type&#39;: &#39;comment&#39;, &#39;value&#39;: &#39;5&#39;},
    {&#39;action_type&#39;: &#39;onsite_conversion.post_save&#39;, &#39;value&#39;: &#39;1&#39;},
    {&#39;action_type&#39;: &#39;link_click&#39;, &#39;value&#39;: &#39;465&#39;},
    {&#39;action_type&#39;: &#39;post&#39;, &#39;value&#39;: &#39;1&#39;},
    {&#39;action_type&#39;: &#39;post_reaction&#39;, &#39;value&#39;: &#39;20&#39;},
    {&#39;action_type&#39;: &#39;video_view&#39;, &#39;value&#39;: &#39;4462&#39;},
    {&#39;action_type&#39;: &#39;post_engagement&#39;, &#39;value&#39;: &#39;4954&#39;},
    {&#39;action_type&#39;: &#39;page_engagement&#39;, &#39;value&#39;: &#39;4954&#39;}],
   &#39;spend&#39;: &#39;214.71&#39;,
   &#39;date_start&#39;: &#39;2023-02-07&#39;,
   &#39;date_stop&#39;: &#39;2023-02-07&#39;}]}

And I am trying to convert it where each element after action type is a pandas DataFrame column, and the value as row. Something like

link_click post_engagement page_engagement   spend comment onsite_conversion ...
        16              16              16   13.59     N/A               N/A
       465            4954            4954  214.71       5                 1

I understand that the first list does not have comment, post, etc, and the rows would be N/A. How do I manage this complicated data structure?

答案1

得分: 1

你可以使用类似以下的函数：

# 导入 pandas 库
import pandas as pd
def tabulate_actions(actionsList:list, returnDf=False):
    aTbl = [{
        a['action_type']: a['value'] for a in al['actions']
        # 如果你对数据结构不确定，取消注释下面的条件语句
        # if isinstance(a, dict) and all([k in a for k in ['action_type', 'value']])
    } for al in actionsList
    # 如果你对数据结构不确定，取消注释下面的条件语句
    # if isinstance(al, dict) and isinstance(al.get('actions'), list)
    ]
    return pd.DataFrame(aTbl) if returnDf else aTbl
## 如果你对数据结构不确定，取消注释下面的条件语句
## uncomment the conditions if you're unsure of your data structure

tabulate_actions(test['data']) 应该返回以下的字典列表：

[{'link_click': '16',
  'post_engagement': '16',
  'page_engagement': '16'},
 {'comment': '5',
  'onsite_conversion.post_save': '1',
  'link_click': '465',
  'post': '1',
  'post_reaction': '20',
  'video_view': '4462',
  'post_engagement': '4954',
  'page_engagement': '4954'}]

传入 returnDf=True 应该返回一个 DataFrame：

英文:

You could use something like this function:

# import pandas as pd
def tabulate_actions(actionsList:list, returnDf=False):
    aTbl = [{
        a[&#39;action_type&#39;]: a[&#39;value&#39;] for a in al[&#39;actions&#39;]
        # if isinstance(a, dict) and all([k in a for k in [&#39;action_type&#39;, &#39;value&#39;]])
    } for al in actionsList
    # if isinstance(al, dict) and isinstance(al.get(&#39;actions&#39;), list)
    ]
    return pd.DataFrame(aTbl) if returnDf else aTbl
## uncomment the conditions if you&#39;re unsure of your data structure

tabulate_actions(test['data']) should return this list of dictionaries:

> python > [{'link_click': '16', > 'post_engagement': '16', > 'page_engagement': '16'}, > {'comment': '5', > 'onsite_conversion.post_save': '1', > 'link_click': '465', > 'post': '1', > 'post_reaction': '20', > 'video_view': '4462', > 'post_engagement': '4954', > 'page_engagement': '4954'}] >

and passing returnDf=True should make it return a DataFrame:

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