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如何使用 Pandas 将嵌套字典 (json) 列表转换为自定义数据框?

[英]How to convert list of nested dicts (json) into a custom dataframe using pandas?

我正在通过 API 组合调查结果,并希望将这些结果转换为如下所示的数据框:

PersonId | Question | Answer | Department

为了实现这一点,每一行必须是一个人的一个问答对,包括第一个问题的部门。 所以在这种情况下,它应该是这样的:

PersonId | Question                                  | Answer | Department
       1 | I can focus on clear targets              |      3 | Department A
       1 | I am satisfied with my working environment|      4 | Department A
       2 | I can focus on clear targets              |      1 | Department B
       2 | I am satisfied with my working environment|      3 | Department B

以下是从 api 检索数据并组合后的数据。 我不需要“答案”和“id”键,因为“结果”包含参与者给出的答案。 答案总是在 1 到 5 之间。

[
      {
        '0': {
          'title': 'What department do you work at?',
          'id': '2571050',
          'results': {
            '0': 'Department A',
            '1': '',
          },
          'answers': {
            '0': 'Department A',
            '1': 'Department B',
          }
        },
        '1': {
          'title': 'I can focus on clear targets',
          'id': '5275962',
          'results': {
            '0': '3'
          },
          'answers': {
            '0': 'Strongly disagree',
            '1': 'Strongly Agree'
          }
        },
        '2': {
          'title': 'I am satisfied with my working environment',
          'id': '5276045',
          'results': {
            '0': '4'
          },
          'answers': {
            '0': 'Strongly Disagree',
            '1': 'Strongly Agree'
          }
        },
      },
      {
        '0': {
          'title': 'What department do you work at?',
          'id': '2571050',
          'results': {
            '0': '',
            '1': 'Department B',
          },
          'answers': {
            '0': 'Department A',
            '1': 'Department B',
          }
        },
        '1': {
          'title': 'I can focus on clear targets',
          'id': '5275962',
          'results': {
            '0': '1'
          },
          'answers': {
            '0': 'Strongly disagree',
            '1': 'Strongly Agree'
          }
        },
        '2': {
          'title': 'I am satisfied with my working environment',
          'id': '5276048',
          'results': {
            '0': '3'
          },
          'answers': {
            '0': 'Strongly Disagree',
            '1': 'Strongly Agree'
          }
        }
      }
 ]

请注意您的 JSON 文件包含一些错误。 字典的最后一个值的末尾不应该有逗号。 您还应该对字典的键/值使用双引号而不是单引号。 我在答案的末尾链接了更正的 JSON 文件。

回到你的问题,你可以使用 json 和 pandas 库来解析你的文件。 这是它的样子:

import json
import pandas as pd

df = pd.DataFrame({'PersonId' : [], 'Question' : [], 'Answer' : [], 'Department' : []})
i = 1
for people in data:
    # We assign an id to the answerer
    person_id = i
    i += 1
    #We retrieve the department of the answerer
    if people['0']['results']['0'] != '':
        department = people['0']['results']['0']
    else:
        department = people['0']['results']['1']
    for answer in people:
        #if we are not asking for the department :
        new_row = {'PersonId' : person_id, 'Department' : department}
        if answer != '0':
            # We collect the question and the answer
            new_row['Question'] = people[answer]['title']
            new_row['Answer'] = people[answer]['results']['0']
            df = df.append(new_row, ignore_index = True)

输出 :

    PersonId                                    Question Answer    Department
0       1.0                I can focus on clear targets      3  Department A
1       1.0  I am satisfied with my working environment      4  Department A
2       2.0                I can focus on clear targets      1  Department B
3       2.0  I am satisfied with my working environment      3  Department B

JSON 文件:

[
      {
        "0": {
          "title": "What department do you work at?",
          "id": "2571050",
          "results": {
            "0": "Department A",
            "1": ""
          },
          "answers": {
            "0": "Department A",
            "1": "Department B"
          }
        },
        "1": {
          "title": "I can focus on clear targets",
          "id": "5275962",
          "results": {
            "0": "3"
          },
          "answers": {
            "0": "Strongly disagree",
            "1": "Strongly Agree"
          }
        },
        "2": {
          "title": "I am satisfied with my working environment",
          "id": "5276045",
          "results": {
            "0": "4"
          },
          "answers": {
            "0": "Strongly Disagree",
            "1": "Strongly Agree"
          }
        }
      },
      {
        "0": {
          "title": "What department do you work at?",
          "id": "2571050",
          "results": {
            "0": "",
            "1": "Department B"
          },
          "answers": {
            "0": "Department A",
            "1": "Department B"
          }
        },
        "1": {
          "title": "I can focus on clear targets",
          "id": "5275962",
          "results": {
            "0": "1"
          },
          "answers": {
            "0": "Strongly disagree",
            "1": "Strongly Agree"
          }
        },
        "2": {
          "title": "I am satisfied with my working environment",
          "id": "5276048",
          "results": {
            "0": "3"
          },
          "answers": {
            "0": "Strongly Disagree",
            "1": "Strongly Agree"
          }
        }
      }
 ]

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