'Build data frame from list with nested dictionaries

I need to build a dataframe from a list of nested dictionaries. The list is something like this:

[
    {'user': {'id': '0011c9a5-d870-4a4d-b32c-689e73f11049'}, 'userContent': {'gy_cv': {}}}
    {'user': {'id': '001e6168-8034-41a1-8d3b-afde984aa5e8'}, 'userContent': {'gy_cv': {}}}
    {'user': {'id': '00248a0e-9bc8-47a9-9955-77363772d5cf'}, 'userContent': {'gy_cv': {'checker': {'intro': 'yes'}}, 'covidMessages': {'messages': {'callDoctorOrTelemed': True, 'callAheadER': False, 'goToER': False, 'quarantine': False, 'dontSpread': True, 'seriousWarning': True, 'lowRisk': False, 'watchForSymptoms': False}}}}
    {'user': {'id': '002ac869-2745-440d-95d2-6641ccb12340'}, 'userContent': {'gy_cv': {'checker': {'intro': 'yes'}}, 'covidMessages': {'messages': {'callDoctorOrTelemed': True, 'callAheadER': False, 'goToER': False, 'quarantine': False, 'dontSpread': True, 'seriousWarning': False, 'lowRisk': False, 'watchForSymptoms': False}}}}
]

And I need to get this output:

Id  Intro   callDoctorOrTelemed callAheadER goToER  quarantine  dontSpread  seriousWarning  lowRisk watchForSymptoms
0011c9a5-d870-4a4d-b32c-689e73f11049                                    
001e6168-8034-41a1-8d3b-afde984aa5e8                                    
00248a0e-9bc8-47a9-9955-77363772d5cf    YES TRUE    FALSE   FALSE   FALSE   TRUE    TRUE    FALSE   FALSE

I've searched but none of the found solutions worked.

Thank you

python

Solution 1:^[1]

You could use glom, to extract the data:

import pandas as pd
from json import loads
from glom import glom

data = loads('[{"user":{"id":"0011c9a5-d870-4a4d-b32c-689e73f11049"},"userContent":{"gy_cv":{}}},{"user":{"id":"001e6168-8034-41a1-8d3b-afde984aa5e8"},"userContent":{"gy_cv":{}}},{"user":{"id":"00248a0e-9bc8-47a9-9955-77363772d5cf"},"userContent":{"gy_cv":{"checker":{"intro":"yes"}},"covidMessages":{"messages":{"callDoctorOrTelemed":true,"callAheadER":false,"goToER":false,"quarantine":false,"dontSpread":true,"seriousWarning":true,"lowRisk":false,"watchForSymptoms":false}}}},{"user":{"id":"002ac869-2745-440d-95d2-6641ccb12340"},"userContent":{"gy_cv":{"checker":{"intro":"yes"}},"covidMessages":{"messages":{"callDoctorOrTelemed":true,"callAheadER":false,"goToER":false,"quarantine":false,"dontSpread":true,"seriousWarning":false,"lowRisk":false,"watchForSymptoms":false}}}}]')

extracted_data = {
    'Id': [glom(d, 'user.id', default=None) for d in data],
    'Intro': [glom(d, 'userContent.gy_cv.checker.intro', default='no') for d in data],
    'callDoctorOrTelemed': [glom(d, 'userContent.covidMessages.messages.callDoctorOrTelemed', default=False) for d in data],
    'callAheadER': [glom(d, 'userContent.covidMessages.messages.callAheadER', default=False) for d in data],
    'goToER': [glom(d, 'userContent.covidMessages.messages.goToER', default=False) for d in data],
    'quarantine': [glom(d, 'userContent.covidMessages.messages.quarantine', default=False) for d in data],
    'dontSpread': [glom(d, 'userContent.covidMessages.messages.dontSpread', default=False) for d in data],
    'seriousWarning': [glom(d, 'userContent.covidMessages.messages.seriousWarning', default=False) for d in data],
    'lowRisk': [glom(d, 'userContent.covidMessages.messages.lowRisk', default=False) for d in data],
    'watchForSymptoms': [glom(d, 'userContent.covidMessages.messages.watchForSymptoms', default=False) for d in data],
}

df = pd.DataFrame(data=extracted_data)
print(df)

Output:

                                     Id Intro  callDoctorOrTelemed  callAheadER  goToER  quarantine  dontSpread  seriousWarning  lowRisk  watchForSymptoms
0  0011c9a5-d870-4a4d-b32c-689e73f11049    no                False        False   False       False       False           False    False             False
1  001e6168-8034-41a1-8d3b-afde984aa5e8    no                False        False   False       False       False           False    False             False
2  00248a0e-9bc8-47a9-9955-77363772d5cf   yes                 True        False   False       False        True            True    False             False
3  002ac869-2745-440d-95d2-6641ccb12340   yes                 True        False   False       False        True           False    False             False

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'Build data frame from list with nested dictionaries

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Solution 1:^[1]