将带有DICT的元素转换为Pandas DataFrame

发布于 2025-02-12 19:18:02 字数 761 浏览 1 评论 0原文

我有一个列表，其中包含dict的元素，我想将其解析到Pandas DataFrame。

[
 (
  {'resource': 'Observation1', 'date': '2021-06-01 11:39:00', 'code': '15848'}, 
  {'date': '2021-04-14 00:00:00','resource': 'Observation2'}
 ),
 (
  {'resource': 'Observation1', 'date': '2011-04-01 11:39:00', 'code': '15848'}, 
  {'date': '2012-06-15 00:00:00','resource': 'Observation2'}
 ),
]

结果框架看起来如下：

x_resource      x_date                x_code   y_date                y_resource       
Observation 1   2021-06-01 11:39:00   15848    2021-04-14 00:00:00   Observation 2
Observation 1   2011-04-01 11:39:00   15848    2012-06-15 00:00:00   Observation 2

我尝试使用pd.multiindex.from_tuples，但无法处理元组中的dicts ...

关于如何解决此问题的任何建议？感谢您的帮助！

原文

I have a list with tuples that contain dicts which I would like to parse to a pandas dataframe.

[
 (
  {'resource': 'Observation1', 'date': '2021-06-01 11:39:00', 'code': '15848'}, 
  {'date': '2021-04-14 00:00:00','resource': 'Observation2'}
 ),
 (
  {'resource': 'Observation1', 'date': '2011-04-01 11:39:00', 'code': '15848'}, 
  {'date': '2012-06-15 00:00:00','resource': 'Observation2'}
 ),
]

The resulting dataframe would look as follows:

x_resource      x_date                x_code   y_date                y_resource       
Observation 1   2021-06-01 11:39:00   15848    2021-04-14 00:00:00   Observation 2
Observation 1   2011-04-01 11:39:00   15848    2012-06-15 00:00:00   Observation 2

I have tried to use the pd.MultiIndex.from_tuples but it can't handle the dicts within the tuples...

Any suggestion on how to solve this?
Thank you for your help!

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ζ澈沫 2025-02-19 19:18:02

对我来说，这个代码工作正常。我认为解决问题对您有帮助。

import pandas as pd

data = [
    (
        {'resource': 'Observation1', 'date': '2021-06-01 11:39:00', 'code': '15848'},
        {'date': '2021-04-14 00:00:00', 'resource': 'Observation2'}
    ),
    (
        {'resource': 'Observation1', 'date': '2011-04-01 11:39:00', 'code': '15848'},
        {'date': '2012-06-15 00:00:00', 'resource': 'Observation2'}
    ),
]

df = pd.DataFrame(data, columns=['x', 'y'])
df = pd.concat([df['x'].apply(pd.Series).add_prefix('x_'), df['y'].apply(pd.Series).add_prefix('y_')], axis=1)

print(df)

For me this code is working fine. I think it would be helpful for you to solve the problem.

import pandas as pd

data = [
    (
        {'resource': 'Observation1', 'date': '2021-06-01 11:39:00', 'code': '15848'},
        {'date': '2021-04-14 00:00:00', 'resource': 'Observation2'}
    ),
    (
        {'resource': 'Observation1', 'date': '2011-04-01 11:39:00', 'code': '15848'},
        {'date': '2012-06-15 00:00:00', 'resource': 'Observation2'}
    ),
]

df = pd.DataFrame(data, columns=['x', 'y'])
df = pd.concat([df['x'].apply(pd.Series).add_prefix('x_'), df['y'].apply(pd.Series).add_prefix('y_')], axis=1)

print(df)

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