vri*_*nda 4 python csv json python-3.x
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}
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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"]])
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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
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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。
您还可以使用 pandas 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')
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