我逐渐熟悉Python中的Classs / OOP,并且正在练习一个用于跟踪财务的基本程序。我已经将程序添加到JSON文件中并保存该文件。现在,我想将JSON文件读入数据框并对其执行一些聚合。那就是我被困住的地方。以下内容失败并显示:
json.decoder.JSONDecodeError: Extra data: line 7 column 2 (char 122)
JSON文件如下所示:
{
"DATE": "2019-02-01 12:57:13.140724",
"HSA": "600",
"401K": "90",
"ROTH": "900",
"SAVINGS": "1000"
}{
"DATE": "2019-02-01 12:57:26.995724",
"HSA": "250",
"401K": "90",
"ROTH": "80",
"SAVINGS": "900"
}
有什么想法吗?
import datetime
import json
import pandas as pd
class BankAccount:
def __init__(self):
self.accounts = ['HSA', '401K', 'ROTH', 'SAVINGS']
self.records = {}
self.now = datetime.datetime.now()
def data_entry(self):
for i in self.accounts:
x = input('Enter the amount for {}:'.format(i))
self.records['DATE'] = self.now
self.records[i] = x
def display(self):
return self.records
def savefile(self):
with open('finance.json', 'a') as file:
file.write(json.dumps(self.records, indent=4, sort_keys=True, default=str))
file.close()
def analyzedata(self):
with open('finance.json', 'r') as f:
obj = json.load(f)
frame = pd.DataFrame(obj, columns=['401K', 'HSA', 'ROTH', 'SAVINGS', 'DATE'])
print(frame)
s = BankAccount()
s.data_entry()
s.savefile()
s.analyzedata()
顺便说一句,BTW随时提供其他建议,说明为什么这样做是一种不好的方式,即使用字典或任何可能的方式。还在学习。谢谢
答案 0 :(得分:1)
JSON数据表示为一个字典,而不是文件中的多个字典。这就是说,我建议JSON格式基本上是一种具有密钥'data'
并包含record
字典列表的字典。我还修复了几个namimg约定,我说过这些小事情可以使我的评论更容易理解。
from datetime import datetime
import json
import pandas as pd
class BankAccount:
def __init__(self, filename='finance.json'):
self.accounts = ['HSA', '401K', 'ROTH', 'SAVINGS']
self.records = []
self.filename = filename
#load data upon initialization
self.load_data()
def load_data(self):
with open(self.filename, 'r') as file:
#you may want to do some error checking here
data = json.load(file)
self.records = data.get('data', [])
def data_entry(self):
#make a new record with current date
record = {'DATE': datetime.now()}
for account_name in self.accounts:
account_data = int(input('Enter the amount for {}:'.format(account_name)))
record[account_name] = account_data
self.records.append(record)
#You made a modification to the records
#now save it to file
self.save_data()
def save_data(self):
with open(self.filename, 'w') as file:
#possibly some error checking here as seen fit
file.write(json.dumps({'data': self.records}, default=str))
def analyze_edata(self):
with open(self.filename, 'r') as file:
df = pd.DataFrame(self.records, columns=self.accounts+['DATE'])
print(df)
s = BankAccount()
s.data_entry()
s.save_data()
s.analyze_data()
当跑步: *几次**
Enter the amount for HSA:250
Enter the amount for 401K:90
Enter the amount for ROTH:80
Enter the amount for SAVINGS:900
['HSA', '401K', 'ROTH', 'SAVINGS', 'DATE']
HSA 401K ROTH SAVINGS DATE
0 600 90 900 1000 2019-02-01 22:05:06.110471
1 360 100 250 430 2019-02-01 22:06:10.649269
2 250 90 80 900 2019-02-01 22:07:04.176700
finance.json
{
"data": [{
"401K": 90,
"SAVINGS": 1000,
"ROTH": 900,
"HSA": 600,
"DATE": "2019-02-01 22:05:06.110471"
}, {
"401K": 100,
"SAVINGS": 430,
"ROTH": 250,
"HSA": 360,
"DATE": "2019-02-01 22:06:10.649269"
}, {
"401K": 90,
"ROTH": 80,
"SAVINGS": 900,
"HSA": 250,
"DATE": "2019-02-01 22:07:04.176700"
}]
}