从字符串的一部分获取数据框[关闭]答案

【问题标题】：Get a data frame from a part of a string [closed]从字符串的一部分获取数据框[关闭]
【发布时间】：2022-01-18 09:55:50
【问题描述】：

我将市场信息作为这样的字符串：

{"POLISUSDT": {"name": "POLISUSDT", "min_amount": "0.5", "maker_fee_rate": "0.003", "taker_fee_rate": "0.003", "pricing_name": "USDT", "pricing_decimal": 4, "trading_name": "POLIS", "trading_decimal": 8}, "XPRBTC": {"name": "XPRBTC", "min_amount": "100", "maker_fee_rate": "0.003", "taker_fee_rate": "0.003", "pricing_name": "BTC", "pricing_decimal": 10, "trading_name": "XPR", "trading_decimal": 8}, "PSPUSDT": {"name": "PSPUSDT", "min_amount": "5", "maker_fee_rate": "0.003", "taker_fee_rate": "0.003", "pricing_name": "USDT", "pricing_decimal": 4, "trading_name": "PSP", "trading_decimal": 8}, "KAVAUSDT": {"name": "KAVAUSDT", "min_amount": "0.5", "maker_fee_rate": "0.003", "taker_fee_rate": "0.003", "pricing_name": "USDT", "pricing_decimal": 4, "trading_name": "KAVA", "trading_decimal": 8}, "CFXUSDT": {"name": "CFXUSDT", "min_amount": "10", "maker_fee_rate": "0.003", "taker_fee_rate": "0.003", "pricing_name": "USDT", "pricing_decimal": 6, "trading_name": "CFX", "trading_decimal": 8}}

我想要每个市场的信息，分别。例如，如果我调用“POLISUSDT”，我想得到这个数据框：

min_amount	maker_fee_rate	taker_fee_rate	pricing_name	pricing_decimal	trading_name	trading_decimal
0.5	0.003	0.003	USDT	4	POLIS	8

【问题讨论】：

您的字符串中有错误。请解决它并更新问题。

标签： python pandas string dataframe substring

【解决方案1】：

请注意，我在解析您的 json 时发现了一些问题 - 在 message 字段之前有一个额外的 }。

除此之外，如果您有 json 的 str 表示（我们称之为 json_str），您可以使用以下方法将其加载到大数据框中：

import pandas as pd

dt = pd.read_json(json_str).transpose()

在这部分代码中，你应该删除你不感兴趣的列。

您可以使用以下方式访问任何元素：

dt.loc[["POLISUSDT"]]

【讨论】：

【解决方案2】：

从样本中删除错误数据后，可以使用带有json_normalize 的字典理解：

d ={"POLISUSDT": {"name": "POLISUSDT", "min_amount": "0.5", "maker_fee_rate": "0.003", "taker_fee_rate": "0.003", "pricing_name": "USDT", "pricing_decimal": 4, "trading_name": "POLIS", "trading_decimal": 8}, "XPRBTC": {"name": "XPRBTC", "min_amount": "100", "maker_fee_rate": "0.003", "taker_fee_rate": "0.003", "pricing_name": "BTC", "pricing_decimal": 10, "trading_name": "XPR", "trading_decimal": 8}, "PSPUSDT": {"name": "PSPUSDT", "min_amount": "5", "maker_fee_rate": "0.003", "taker_fee_rate": "0.003", "pricing_name": "USDT", "pricing_decimal": 4, "trading_name": "PSP", "trading_decimal": 8}, "KAVAUSDT": {"name": "KAVAUSDT", "min_amount": "0.5", "maker_fee_rate": "0.003", "taker_fee_rate": "0.003", "pricing_name": "USDT", "pricing_decimal": 4, "trading_name": "KAVA", "trading_decimal": 8}, "CFXUSDT": {"name": "CFXUSDT", "min_amount": "10", "maker_fee_rate": "0.003", "taker_fee_rate": "0.003", "pricing_name": "USDT", "pricing_decimal": 6, "trading_name": "CFX", "trading_decimal": 8}}

df = {k: pd.json_normalize(v) for k, v in d.items()}
print (df['POLISUSDT'])
        name min_amount maker_fee_rate taker_fee_rate pricing_name  \
0  POLISUSDT        0.5          0.003          0.003         USDT   

   pricing_decimal trading_name  trading_decimal  
0                4        POLIS                8

【讨论】：

【解决方案3】：

你可以这样做：

df = pd.DataFrame(data)
df_dict = {col: df[col].drop('name', axis=0).rename(None).to_frame().T for col in df.columns}

print(df_dict['POLISUSDT'])

输出：

  min_amount maker_fee_rate taker_fee_rate pricing_name pricing_decimal  trading_name  trading_decimal  
0        0.5          0.003          0.003         USDT               4   POLIS               8  

   trading_decimal

【讨论】：