使用Python从JSON API提取值

我使用api获取特定共享的信息

{
  "Meta Data": {
    "1. Information": "Daily Prices (open, high, low, close) and Volumes",
    "2. Symbol": "MSFT",
    "3. Last Refreshed": "2020-05-22",
    "4. Output Size": "Compact",
    "5. Time Zone": "US/Eastern"
  },
  "Time Series (Daily)": {
    "2020-05-22": {
      "1. open": "183.1900",
      "2. high": "184.4600",
      "3. low": "182.5400",
      "4. close": "183.5100",
      "5. volume": "20826898"
    },
    "2020-05-21": {
      "1. open": "185.4000",
      "2. high": "186.6700",
      "3. low": "183.2900",
      "4. close": "183.4300",
      "5. volume": "29032741"
    }, and more...

我现在只想提取日期，打开，高转换成一个CSV

import requests
import json

url = "https://alpha-vantage.p.rapidapi.com/query"

querystring = {"outputsize":"compact","datatype":"JSON","function":"TIME_SERIES_DAILY","symbol":"MSFT"}

headers = {
    'x-rapidapi-host': "alpha-vantage.p.rapidapi.com",
    'x-rapidapi-key': "API KEY"
    }

response = requests.request("GET", url, headers=headers, params=querystring)

info = response.json()

with open('data.json', 'w') as fp:
    json.dump(info, fp)

f = open('data.json',)

data = json.load(f)

meta = data["Meta Data"]

for i in data['Meta Data']:
    print(i)

# Closing file
f.close()

输出：

1. Information
2. Symbol
3. Last Refreshed
4. Output Size
5. Time Zone

我以为信息是在“元数据”中，但显然不是。

---

有人能确切地向我解释一下我做错了什么吗？

你的口述中有好几条

meta = data["Meta Data"]

# Contains dict

 "1. Information": "Daily Prices (open, high, low, close) and Volumes",
 "2. Symbol": "MSFT",
 "3. Last Refreshed": "2020-05-22",
 "4. Output Size": "Compact",
 "5. Time Zone": "US/Eastern"

timeSeries = data['Time Series (Daily)']['2020-05-22']

# Contains dict


  "1. open": "183.1900",
  "2. high": "184.4600",
  "3. low": "182.5400",
  "4. close": "183.5100",
  "5. volume": "20826898"

您只需访问如下值：

eventOpen = data['Time Series (Daily)']['2020-05-22']['1. open']

---

尝试使用这些对象并打印它们的类型和内容，以便您了解它们包含的内容以及如何访问它们。

时间序列（每日）的结果非常混乱。 无法转换为正确的CSV格式

使用pandas，我格式化了数据，并能够将数据转换为正确的CSV格式

meta = json.load(f)
data = meta['Meta Data']
data = meta['Time Series (Daily)']

df=pd.DataFrame(columns=['date','open','high','low','close','volume'])
for d,p in data.items():
    date=datetime.datetime.strptime(d,'%Y-%m-%d').date()
    data_row=[date,float(p['1. open']),float(p['2. high']),float(p['3. low']),float(p['4. close']),int(p['5. volume'])]
    df.loc[-1,:]=data_row
    df.index=df.index+1
df =df.sort_values('date')
df.to_csv('test.csv')

---

谢谢你的回答。但是，如果我循环浏览“时间序列（每日）”，我只会得到日期。是的，我的错，与你的括号混淆了，我正在更新答案。

          date     open     high      low    close    volume
0   2019-12-27  3776.82  3794.93  3775.26  3782.27  24437900
1   2019-12-30  3780.44  3780.44  3748.47  3748.47  18684000
2   2020-01-03  3787.57  3787.57  3745.54  3773.37  30343400
3   2020-01-06  3764.34  3764.34  3710.94  3752.52  28339400
4   2020-01-07  3760.09  3784.42  3748.13  3759.25  29853300
.... to continue ()...