用python对json接收到的数据进行制表答案

【问题标题】：Tabulating data received with json with python用python对json接收到的数据进行制表
【发布时间】：2020-10-30 16:16:48
【问题描述】：

我可以解析以下数据。但我无法将其显示为柱状表格。我如何绘制这个图表？

 for item in items:
     print(item['symbol'])

[
{"symbol": "ZILUSDT", "positionAmt": "0", "entryPrice": "0.00000", "markPrice": "0.01728152", "unRealizedProfit": "0.00000000", "liquidationPrice": "0", "leverage": "20", "maxNotionalValue": "25000", "marginType": "cross", "isolatedMargin": "0.00000000", "isAutoAddMargin": "false", "positionSide": "SHORT"}, 
{"symbol": "FLMUSDT", "positionAmt": "0", "entryPrice": "0.0000", "markPrice": "0.00000000", "unRealizedProfit": "0.00000000", "liquidationPrice": "0", "leverage": "20", "maxNotionalValue": "25000", "marginType": "cross", "isolatedMargin": "0.00000000", "isAutoAddMargin": "false", "positionSide": "BOTH"}, 
{"symbol": "FLMUSDT", "positionAmt": "0", "entryPrice": "0.0000", "markPrice": "0.00000000", "unRealizedProfit": "0.00000000", "liquidationPrice": "0", "leverage": "20", "maxNotionalValue": "25000", "marginType": "cross", "isolatedMargin": "0.00000000", "isAutoAddMargin": "false", "positionSide": "LONG"}, 
{"symbol": "FLMUSDT", "positionAmt": "0", "entryPrice": "0.0000", "markPrice": "0.00000000", "unRealizedProfit": "0.00000000", "liquidationPrice": "0", "leverage": "20", "maxNotionalValue": "25000", "marginType": "cross", "isolatedMargin": "0.00000000", "isAutoAddMargin": "false", "positionSide": "SHORT"}
]



How can I show it in a table like the one below?

     headers = ["Symbol", "EntryPrice", "side", "position"]
     symbols = [x['symbol'] for x in data]
     table = columnar(symbols, headers=headers)
     print(table)

【问题讨论】：

“图表”是什么意思？您的意思是要创建实际图像（即 JPEG 或 GIF）？
pypi.org/project/Columnar 没有我想在这里创建的人

标签： python json python-3.x python-2.7

【解决方案1】：

您有一个字典列表。最简单的方法是将它们包装到 pandas 的 DataFrame 中，它可以开箱即用地处理该类型。

import pandas as pd

tabulated = pd.DataFrame(items)
print(tabulated)

【讨论】：

对于项目中的 sym：tabulated = pd.DataFrame(sym['symbol'], sym['entryPrice']) print(tabulated)

【解决方案2】：

Pandas 是一个很好的解决方案，但您也可以原生地以表格格式呈现数据：

for row in zip(*([key] + (value) for key, value in sorted(items.items()))):
    print(*row)

【讨论】：