将 Alphavantage API 响应转换为 DataFrame

Question

我在 SO 上查找了其他相关主题，只找到了类似的问题，但没有任何帮助。

我正在查询 AlphaVantage 以获取股票数据。我收到了数据并进行了解码，但由于格式问题目前无法转换为 pandas 数据帧。响应采用以下形式：

{
    "Meta Data": {
        "1. Information": "Daily Prices (open, high, low, close) and Volumes",
        "2. Symbol": "AAPL",
        "3. Last Refreshed": "2021-04-26",
        "4. Output Size": "Full size",
        "5. Time Zone": "US/Eastern"
    },
    "Time Series (Daily)": {
        "2021-04-26": {
            "1. open": "134.8300",
            "2. high": "135.0600",
            "3. low": "133.5600",
            "4. close": "134.7200",
            "5. volume": "66905069"
        },
        "2021-04-23": {
            "1. open": "132.1600",
            "2. high": "135.1200",
            "3. low": "132.1600",
            "4. close": "134.3200",
            "5. volume": "78756779"
        },
        "2021-04-22": {
            "1. open": "133.0400",
            "2. high": "134.1500",
            "3. low": "131.4100",
            "4. close": "131.9400",
            "5. volume": "84566456"
        },

在运行下面的代码之后：

import requests as rq
import json

base_url = "https://www.alphavantage.co/query?"
params = {"function":function, "symbol":symbol, "outputsize":output_size, "datatype":data_type, "apikey":api_key}

response = rq.get(base_url, params=params)
data_str = data_bytes.decode("utf-8")

我在尝试将数据加载到数据帧时出现问题：

data_dict = json.loads(data_str)
df = pd.DataFrame(data_dict.items())
df.head()

Returns:

    0   1
0   Meta Data   {'1. Information': 'Daily Prices (open, high, ...
1   Time Series (Daily)     {'2021-04-26': {'1. open': '134.8300', '2. hig...

还有...

data_dict = json.loads(data_str)
df = pd.DataFrame(data_dict)
df.head()

Returns:

    Meta Data   Time Series (Daily)
1. Information  Daily Prices (open, high, low, close) and Volumes   NaN
2. Symbol   AAPL    NaN
3. Last Refreshed   2021-04-26  NaN
4. Output Size  Full size   NaN
5. Time Zone    US/Eastern  NaN

哪个都不可用。我正在寻找以下形式的数据框：

date   open   high   low   close   volume

有没有办法将响应转换成这种格式？

Answer 1

因为您只需要 Time Series (Daily) 个值。所以在创建dataframe的时候可以直接使用

data_dict = json.loads(data_str)
df = pd.DataFrame(data_dict["Time Series (Daily)"])
df = df.T  # Transpose Dataframe for desired results

将 Alphavantage API 响应转换为 DataFrame

Convert Alphavantage API Response to DataFrame

python

pandas

dataframe

alpha-vantage