如何解决如何将json文件转换为pandas可读
我有一个用于机器学习实现的实时库存 API 我使用 Google colab 作为环境 我已经与 API 建立了联系，状态为成功，我收到了一个 json 文本文件，我已解析为 .json() 并使其成为可查看和缩进的。
{
"Meta Data": {
"1. Information": "Daily Prices and Volumes for Digital Currency","2. Digital Currency Code": "BTC","3. Digital Currency Name": "Bitcoin","4. Market Code": "CNY","5. Market Name": "Chinese Yuan","6. Last Refreshed": "2021-01-22 00:00:00","7. Time Zone": "UTC"
},"Time Series (Digital Currency Daily)": {
"2021-01-22": {
"1a. open (CNY)": "199365.55938000","1b. open (USD)": "30851.99000000","2a. high (CNY)": "199443.03876000","2b. high (USD)": "30863.98000000","3a. low (CNY)": "188839.21986000","3b. low (USD)": "29223.03000000","4a. close (CNY)": "192933.34920000","4b. close (USD)": "29856.60000000","5. volume": "12132.72474600","6. market cap (USD)": "12132.72474600"
},"2021-01-21": {
"1a. open (CNY)": "229195.70226000","1b. open (USD)": "35468.23000000","2a. high (CNY)": "230047.20000000","2b. high (USD)": "35600.00000000","3a. low (CNY)": "194318.80200000","3b. low (USD)": "30071.00000000","4a. close (CNY)": "199353.54006000","4b. close (USD)": "30850.13000000","5. volume": "131803.18292600","6. market cap (USD)": "131803.18292600"
现在的问题是我们如何使这个 json 文件成为熊猫可读的。欢迎提出任何建议
解决方法
读入时间序列，然后transpose(),T。然后重命名您的列。
df = pd.DataFrame(d["Time Series (Digital Currency Daily)"]).T
df.columns = ['open CNY','open USD','high CNY','high USD','low CNY','low USD','close CNY','close USD','volume','market cap USD']
输出
open CNY open USD high CNY high USD low CNY low USD close CNY close USD volume market cap USD
2021-01-22 199365.55938 30851.99 199443.03876 30863.98 188839.21986 29223.03 192933.34920 29856.60 12132.724746 12132.724746
2021-01-21 229195.70226 35468.23 230047.20000 35600.00 194318.80200 30071.00 199353.54006 30850.13 131803.182926 131803.182926
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