我有一个json文件,如下所示。我已经试过这篇文章的解决方案了
[{
"answersData": {
"employeeId": "0923a",
"answers": {
"Address_2": "Address_Line_2_1",
"Address_2_CC": "Address_2_CC_1",
"CellphoneNumberConsent": "YES",
"Consent_Given": "Y",
"DoB": "1971-07-10T16:00:00.000Z",
"EmailaddressConsent": "NotApplicable",
"First_Name": "First_Name_1",
"Gender": "M",
"Last_Name": "Last_Name_1",
"Middle_Name": null,
"PrimaryLanguage": [
"English"
],
"SecondaryLanguage": [
"Hindi"
],
"addionalIdentificationType": "NO",
"cellphoneNumber": "1234567890",
"countryName": "IND",
"householdResponsibility": "husband",
"poorCardHas": "N",
"poorCardReason": "OTH",
"postalCode": "123456",
"profilePicture": null,
"provinceCity": "Province_1"
},
"createdBy": "MAM_1@123.com",
"dateCreated": "2021-02-23T17:20:33.134Z",
"type": "profile"
}
}, {
"answersData": {
"employeeId": "27l23t",
"answers": {
"Address_2": "Address_Line_2_2",
"Address_2_CC": "Address_2_CC_2",
"CellphoneNumberConsent": "YES",
"Consent_Given": "Y",
"DoB": "1980-07-10T16:00:00.000Z",
"EmailaddressConsent": "NotApplicable",
"First_Name": "First_Name_2",
"Gender": "M",
"Last_Name": "Last_Name_2",
"Middle_Name": null,
"PrimaryLanguage": [
"English"
],
"SecondaryLanguage": [
"Kannada"
],
"addionalIdentificationType": "NO",
"cellphoneNumber": "1234567890",
"countryName": "IND",
"householdResponsibility": "wife",
"poorCardHas": "N",
"poorCardReason": "OTH",
"postalCode": "621",
"profilePicture": null,
"provinceCity": "Province_2"
},
"createdBy": "MAM_2@123.com",
"dateCreated": "2021-02-23T17:20:33.134Z",
"type": "profile"
}
}, {
"answersData": {
"employeeId": "290p",
"answers": {
"Address_2": "Address_Line_2_3",
"Address_2_CC": "Address_2_CC_3",
"CellphoneNumberConsent": "NO",
"Consent_Given": "N",
"DoB": "1991-10-10T16:00:00.000Z",
"EmailaddressConsent": "NotApplicable",
"First_Name": "First_Name_3",
"Gender": "M",
"Last_Name": "Last_Name_3",
"Middle_Name": null,
"PrimaryLanguage": [
"German"
],
"SecondaryLanguage": [
"Telugu"
],
"addionalIdentificationType": "NO",
"cellphoneNumber": "1234567890",
"countryName": "IND",
"householdResponsibility": "Father",
"poorCardHas": "N",
"poorCardReason": "OTH",
"postalCode": "123456",
"profilePicture": null,
"provinceCity": "Province_3"
},
"createdBy": "MAM_3@123.com",
"dateCreated": "2021-01-11T19:11:20.134Z",
"type": "profile"
}
}, {
"answersData": {
"employeeId": "17mk9i",
"answers": {
"Address_2": "Address_Line_2_4",
"Address_2_CC": "Address_2_CC_4",
"CellphoneNumberConsent": "YES",
"Consent_Given": "Y",
"DoB": "1947-07-10T16:00:00.000Z",
"EmailaddressConsent": "NotApplicable",
"First_Name": "First_Name_4",
"Gender": "M",
"Last_Name": "Last_Name_4",
"Middle_Name": null,
"PrimaryLanguage": [
"English"
],
"SecondaryLanguage": [
"Hindi"
],
"addionalIdentificationType": "NO",
"cellphoneNumber": "1234567890",
"countryName": "IND",
"householdResponsibility": "mother",
"poorCardHas": "N",
"poorCardReason": "OTH",
"postalCode": "123456",
"profilePicture": null,
"provinceCity": "Province_4"
},
"createdBy": "MAM_4@123.com",
"dateCreated": "2021-05-23T17:20:33.134Z",
"type": "profile"
}
}, {
"answersData": {
"employeeId": "17lo8i",
"answers": {
"Address_2": "Address_Line_2_5",
"Address_2_CC": "Address_2_CC_5",
"CellphoneNumberConsent": "YES",
"Consent_Given": "Y",
"DoB": "1993-07-10T16:00:00.000Z",
"EmailaddressConsent": "NotApplicable",
"First_Name": "First_Name_5",
"Gender": "M",
"Last_Name": "Last_Name_5",
"Middle_Name": null,
"PrimaryLanguage": [
"English"
],
"SecondaryLanguage": [
"Hindi"
],
"addionalIdentificationType": "NO",
"cellphoneNumber": "1234567890",
"countryName": "IND",
"householdResponsibility": "child",
"poorCardHas": "N",
"poorCardReason": "OTH",
"postalCode": "123456",
"profilePicture": null,
"provinceCity": "Province_5"
},
"createdBy": "MAM_5@123.com",
"dateCreated": "2021-01-01T17:20:33.134Z",
"type": "profile"
}
}, {
"answersData": {
"employeeId": "17k9i",
"answers": {
"Address_2": "Address_Line_2_6",
"Address_2_CC": "Address_2_CC_6",
"CellphoneNumberConsent": "YES",
"Consent_Given": "Y",
"DoB": "1983-07-10T16:00:00.000Z",
"EmailaddressConsent": "NotApplicable",
"First_Name": "First_Name_6",
"Gender": "M",
"Last_Name": "Last_Name_6",
"Middle_Name": null,
"PrimaryLanguage": [
"Spanish"
],
"SecondaryLanguage": [
"Tagalog"
],
"addionalIdentificationType": "NO",
"cellphoneNumber": "1234567890",
"countryName": "IND",
"householdResponsibility": "husband",
"poorCardHas": "N",
"poorCardReason": "OTH",
"postalCode": "123456",
"profilePicture": null,
"provinceCity": "Province_6"
},
"createdBy": "MAM_6@123.com",
"dateCreated": "2021-01-16T17:20:33.134Z",
"type": "profile"
}
}, {
"answersData": {
"employeeId": "87p",
"answers": {
"Address_2": "TEST123",
"Address_2_CC": "Test",
"CellphoneNumberConsent": "YES",
"Consent_Given": "Y",
"DoB": "1801-07-10T16:00:00.000Z",
"EmailaddressConsent": "NotApplicable",
"First_Name": "Test123",
"Gender": "M",
"Last_Name": "Test123",
"Middle_Name": null,
"PrimaryLanguage": [
"English"
],
"SecondaryLanguage": [
"Kannada"
],
"addionalIdentificationType": "NO",
"cellphoneNumber": "1234567890",
"countryName": "IND",
"householdResponsibility": "wife",
"poorCardHas": "N",
"poorCardReason": "OTH",
"postalCode": "654321",
"profilePicture": null,
"provinceCity": "Province_2"
},
"createdBy": "jo@test.com",
"dateCreated": "2021-02-23T17:20:33.134Z",
"type": "profile"
}
}, {
"answersData": {
"employeeId": "09l07ytw",
"answers": {
"Address_2": "TEST123",
"Address_2_CC": "Test",
"CellphoneNumberConsent": "YES",
"Consent_Given": "Y",
"DoB": "1801-07-10T16:00:00.000Z",
"EmailaddressConsent": "NotApplicable",
"First_Name": "Test123",
"Gender": "M",
"Last_Name": "Test123",
"Middle_Name": null,
"PrimaryLanguage": [
"English"
],
"SecondaryLanguage": [
"Kannada"
],
"addionalIdentificationType": "NO",
"cellphoneNumber": "1234567890",
"countryName": "IND",
"householdResponsibility": "wife",
"poorCardHas": "N",
"poorCardReason": "OTH",
"postalCode": "654321",
"profilePicture": null,
"provinceCity": "Province_2"
},
"createdBy": "jo@test.com",
"dateCreated": "2021-02-23T17:20:33.134Z",
"type": "profile"
}
}
]
当我试图阅读 json
文件使用Pandas,我得到下面的错误
valueerror:预期的对象或值
我已经试过下面的方法了
df = pd.read_json(open(r"test_data.json", "r",encoding="utf8"))
df = pd.read_json(r'test_data.json', encoding='utf-8-sig')
basepath = 'C:\\Users\\test\\Downloads'
pd.read_json(basePath + '\\test_data.json')
当前我的输出如下所示
但我希望我的输出如下所示
2条答案
按热度按时间ebdffaop1#
使用json\u normalize展平嵌套数据。
代码
测向
xkftehaa2#
错误表明它不理解代码的一部分。
你应该检查代码的格式。要做到这一点的页面是:https://jsonformatter.curiousconcept.com/