Pandas 规范化字典列表

Question

我目前正在尝试编辑 Mongo DB 中的数据。我已经能够将数据读入数据框中。但是，我有一个问题，即在数据框中，一列包含一个字典列表。我已经尝试使用 pd.json.normalize 编辑数据，但我得到错误'float' object has no attributes 'values'。如何将列转换为新的数据框？

数据框如下所示：

status	message	vars
1.	ok	[{'key': 'A1', 'value': '1', 'vartype: '1'}, {'key': 'A2', 'value': '0', 'vartype: '1'}, {'key': 'A3', 'value': '1', 'vartype: '1]

执行此行时，我收到以下错误消息：

df3 = pd.json_normalize(df3['vars'])

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-164-da47e4ddf140> in <module>
----> 1 df3 = pd.json_normalize(df3['vars'])

/opt/conda/lib/python3.8/site-packages/pandas/io/json/_normalize.py in _json_normalize(data, record_path, meta, meta_prefix, record_prefix, errors, sep, max_level)
    268 
    269     if record_path is None:
--> 270         if any([isinstance(x, dict) for x in y.values()] for y in data):
    271             # naive normalization, this is idempotent for flat records
    272             # and potentially will inflate the data considerably for

/opt/conda/lib/python3.8/site-packages/pandas/io/json/_normalize.py in <genexpr>(.0)
    268 
    269     if record_path is None:
--> 270         if any([isinstance(x, dict) for x in y.values()] for y in data):
    271             # naive normalization, this is idempotent for flat records
    272             # and potentially will inflate the data considerably for

AttributeError: 'float' object has no attribute 'values'

Answer 1

IIUC 使用：

df3 = pd.json_normalize(df3['vars'].dropna())