如何在python中将json转换为csv

Question

以下是我的 json 文件输入

{"userID": "679d3bad-155e-4b39-9ff7-7d564f408942", "Is salary credited before 5th": "Yes", "Avg Salary of last 3 months": 15453.33, "Avg Salary of last 6 months": 15290.5, "Avg Balance before salary of last 3 months": 113.15, "Avg Balance before salary of last 6 months": 105.22}

代码

    with open('/Users/vrindabv/Documents/PycharmProjects/BankStatementEngine/test.json', "r") as f:
        BankData = json.loads(f.read())
    x = json.loads(json.dumps(BankData))
    f = csv.writer(open("/Users/vrindabv/Documents/PycharmProjects/BankStatementEngine/test.csv", "w"))
    f.writerow(["userID", "Is salary credited before 5th", "Avg Salary of last 3 months", "Avg Salary of last 6 months", "Avg Balance before salary of last 3 months", "Avg Balance before salary of last 6 months"])

    for y in x:
        f.writerow([x["userID"], x["Is salary credited before 5th"],
                    x["Avg Salary of last 3 months"],
                    x["Avg Salary of last 6 months"],
                    x["Avg Balance before salary of last 3 months"],
                    x["Avg Balance before salary of last 6 months"]])

输出

userID,Is salary credited before 5th,Avg Salary of last 3 months,Avg Salary of last 6 months,Avg Balance before salary of last 3 months,Avg Balance before salary of last 6 months
679d3bad-155e-4b39-9ff7-7d564f408942,Yes,15453.33,15290.5,113.15,105.22
679d3bad-155e-4b39-9ff7-7d564f408942,Yes,15453.33,15290.5,113.15,105.22
679d3bad-155e-4b39-9ff7-7d564f408942,Yes,15453.33,15290.5,113.15,105.22
679d3bad-155e-4b39-9ff7-7d564f408942,Yes,15453.33,15290.5,113.15,105.22
679d3bad-155e-4b39-9ff7-7d564f408942,Yes,15453.33,15290.5,113.15,105.22
679d3bad-155e-4b39-9ff7-7d564f408942,Yes,15453.33,15290.5,113.15,105.22
679d3bad-155e-4b39-9ff7-7d564f408942,Yes,15453.33,15290.5,113.15,105.22

所以，在这里我确实得到了答案，但不是打印一次，而是打印了 7 次。我该如何解决这个问题。

原文由 vrinda 发布，翻译遵循 CC BY-SA 4.0 许可协议

Answer 1

BankData 是一个你不需要迭代它的字典。您可以使用键直接访问值。

前任：

 import csv
import json

with open('/Users/vrindabv/Documents/PycharmProjects/BankStatementEngine/test.json') as infile:
    BankData = json.loads(infile.read())

with open("/Users/vrindabv/Documents/PycharmProjects/BankStatementEngine/test.csv", "w") as outfile:
    f = csv.writer(outfile)
    f.writerow(["userID", "Is salary credited before 5th", "Avg Salary of last 3 months", "Avg Salary of last 6 months", "Avg Balance before salary of last 3 months", "Avg Balance before salary of last 6 months"])
    f.writerow([BankData["userID"], BankData["Is salary credited before 5th"],
                BankData["Avg Salary of last 3 months"],
                BankData["Avg Salary of last 6 months"],
                BankData["Avg Balance before salary of last 3 months"],
                BankData["Avg Balance before salary of last 6 months"]])

原文由 Rakesh 发布，翻译遵循 CC BY-SA 4.0 许可协议

Answer 2

您还可以使用熊猫来处理数据框，

 dct = {"userID": "679d3bad-155e-4b39-9ff7-7d564f408942", "Is salary credited before 5th": "Yes", "Avg Salary of last 3 months": 15453.33,
       "Avg Salary of last 6 months": 15290.5, "Avg Balance before salary of last 3 months": 113.15, "Avg Balance before salary of last 6 months": 105.22}

import pandas as pd

df = pd.DataFrame.from_records(dct, index=[0])

df.to_csv('outputfile.csv')

原文由 Menglong Li 发布，翻译遵循 CC BY-SA 4.0 许可协议