在Python中格式化/图形化动态JSON数据

我试图利用的JSON图形数据不包含设置键。它返回过去180天的数据。第一个数字是自历元以来的毫秒数，值是游戏中的价格。我需要知道如何解析这些数据，以便在以后使用函数将第一个值转换为毫秒日期时分配变量：

def convert_from_ms( milliseconds ): 
    seconds, milliseconds = divmod(milliseconds,1000) 
    minutes, seconds = divmod(seconds, 60) 
    hours, minutes = divmod(minutes, 60) 
    days, hours = divmod(hours, 24) 
    seconds = seconds + milliseconds/1000 
    return days, hours, minutes, seconds 

然后是一个绘图/绘图库（关于这方面的建议也会受到欢迎，可能只会使用matplot）

数据如下所示：

{"daily":{"1582416000000":193,"1582502400000":193,"1582588800000":190,"1582675200000":189,"1582761600000":189,"1582848000000":191,"1582934400000":191,"1583020800000":190,"1583107200000":190,"1583193600000":191,"1583280000000":192,"1583366400000":191,"1583452800000":191,"1583539200000":189,"1583625600000":186,"1583712000000":182,"1583798400000":177,"1583884800000":173,"1583971200000":170,"1584057600000":167,"1584144000000":165,"1584230400000":170,"1584316800000":176,"1584403200000":179,"1584489600000":179,"1584576000000":182,"1584662400000":187,"1584748800000":187,"1584835200000":185,"1584921600000":183,"1585008000000":185,"1585094400000":185,"1585180800000":183,"1585267200000":183,"1585353600000":185,"1585440000000":185,"1585526400000":184,"1585612800000":186,"1585699200000":189,"1585785600000":190,"1585872000000":192,"1585958400000":193,"1586044800000":192,"1586131200000":192,"1586217600000":192,"1586304000000":193,"1586390400000":195,"1586476800000":196,"1586563200000":196,"1586649600000":191,"1586736000000":182,"1586822400000":174,"1586908800000":168,"1586995200000":171,"1587081600000":176,"1587168000000":179,"1587254400000":180,"1587340800000":174,"1587427200000":167,"1587513600000":168,"1587600000000":172,"1587686400000":180,"1587772800000":185,"1587859200000":186,"1587945600000":184,"1588032000000":189,"1588118400000":196,"1588204800000":200,"1588291200000":204,"1588377600000":207,"1588464000000":209,"1588550400000":207,"1588636800000":207,"1588723200000":207,"1588809600000":207,"1588896000000":206,"1588982400000":200,"1589068800000":191,"1589155200000":183,"1589241600000":184,"1589328000000":190,"1589414400000":194,"1589500800000":198,"1589587200000":197,"1589673600000":192,"1589760000000":184,"1589846400000":182,"1589932800000":186,"1590019200000":186,"1590105600000":188,"1590192000000":186,"1590278400000":184,"1590364800000":181,"1590451200000":177,"1590537600000":172,"1590624000000":174,"1590710400000":180,"1590796800000":177,"1590883200000":174,"1590969600000":172,"1591056000000":173,"1591142400000":171,"1591228800000":172,"1591315200000":174,"1591401600000":170,"1591488000000":170,"1591574400000":172,"1591660800000":173,"1591747200000":174,"1591833600000":175,"1591920000000":176,"1592006400000":175,"1592092800000":174,"1592179200000":171,"1592265600000":170,"1592352000000":169,"1592438400000":167,"1592524800000":165,"1592611200000":162,"1592697600000":159,"1592784000000":157,"1592870400000":162,"1592956800000":167,"1593043200000":168,"1593129600000":167,"1593216000000":162,"1593302400000":159,"1593388800000":157,"1593475200000":159,"1593561600000":165,"1593648000000":170,"1593734400000":172,"1593820800000":172,"1593907200000":173,"1593993600000":174,"1594080000000":176,"1594166400000":178,"1594252800000":182,"1594339200000":182,"1594425600000":177,"1594512000000":175,"1594598400000":177,"1594684800000":176,"1594771200000":179,"1594857600000":181,"1594944000000":180,"1595030400000":177,"1595116800000":175,"1595203200000":174,"1595289600000":176,"1595376000000":175,"1595462400000":171,"1595548800000":170,"1595635200000":169,"1595721600000":169,"1595808000000":170,"1595894400000":172,"1595980800000":171,"1596067200000":171,"1596153600000":170,"1596240000000":170,"1596326400000":172,"1596412800000":174,"1596499200000":175,"1596585600000":176,"1596672000000":178,"1596758400000":180,"1596844800000":180,"1596931200000":179,"1597017600000":178,"1597104000000":174,"1597190400000":170,"1597276800000":165,"1597363200000":160,"1597449600000":162,"1597536000000":165,"1597622400000":165,"1597708800000":166,"1597795200000":164,"1597881600000":163},"average":{"1582416000000":201,"1582502400000":200,"1582588800000":198,"1582675200000":196,"1582761600000":195,"1582848000000":193,"1582934400000":191,"1583020800000":190,"1583107200000":189,"1583193600000":189,"1583280000000":188,"1583366400000":189,"1583452800000":189,"1583539200000":189,"1583625600000":189,"1583712000000":189,"1583798400000":189,"1583884800000":189,"1583971200000":188,"1584057600000":187,"1584144000000":186,"1584230400000":186,"1584316800000":185,"1584403200000":185,"1584489600000":185,"1584576000000":184,"1584662400000":184,"1584748800000":184,"1584835200000":184,"1584921600000":183,"1585008000000":183,"1585094400000":183,"1585180800000":183,"1585267200000":182,"1585353600000":182,"1585440000000":182,"1585526400000":182,"1585612800000":182,"1585699200000":182,"1585785600000":182,"1585872000000":182,"1585958400000":182,"1586044800000":182,"1586131200000":182,"1586217600000":182,"1586304000000":182,"1586390400000":183,"1586476800000":184,"1586563200000":185,"1586649600000":186,"1586736000000":186,"1586822400000":186,"1586908800000":186,"1586995200000":186,"1587081600000":186,"1587168000000":185,"1587254400000":185,"1587340800000":185,"1587427200000":184,"1587513600000":184,"1587600000000":183,"1587686400000":183,"1587772800000":183,"1587859200000":183,"1587945600000":183,"1588032000000":183,"1588118400000":184,"1588204800000":184,"1588291200000":18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我尝试过许多类似的变化：

data = json.loads(graph_get.text)

    raw_graph_data = {}
    graph_dates = {}
    graph_prices = {}
    if('daily' in data):
        for key in data['daily']:
            raw_graph_data[key] = data['daily'][key]

    for x in raw_graph_data:
        isolate_dates = x.replace("'", '')
        info = isolate_dates.split("': ")
        graph_dates[x] = info[0]
        graph_prices[x] = info[1]

---

但我知道这不是正确的方法。。我知道我不能使用x写入数组。我只是被难住了。我以前从未使用过这样的“动态”JSON数据。非常感谢您的指点。

我不能100%确定您想要完成什么，但是您可以使用以下代码来处理和绘制数据。我没有使用自定义方法将毫秒转换为日期，而是使用了datetime模块

从日期时间导入日期时间
将matplotlib.pyplot作为plt导入
日期=[]
价格=[]
对于键，data.get（'daily'，{}.items（）中的值：
dates.append（datetime.fromtimestamp（int（key）/1000））
价格。附加（价值）
地块（日期、价格）
plt.show（）