Question

我的第一个数据帧df_gammask如下所示：

    distance breakEvenDistance  min max
0   2.1178  2.0934  NaN         0.000955
1   2.0309  2.1473  0.000955    0.001041
2   1.9801  1.7794  0.001041    0.001124
3   1.9282  2.1473  0.001124    0.001199
4   1.8518  1.5885  0.001199    0.001259
5   1.8518  1.5151  0.001259    0.001319

第二个df_gammabid：

distance    breakEvenDistance   min max
0   1.9999  1.9329  NaN         0.001034
1   1.9251  2.0670  0.001034    0.001118
2   1.8802  1.6758  0.001118    0.001193
3   1.8802  1.5956  0.001193    0.001252
4   1.7542  1.5181  0.001252    0.001317
5   1.7542  1.4541  0.001317    0.001374

我需要的是一个像这样的json文件：

{
  "buy": [
    {
      "distance": 0.6278,
      "breakEvenDistance": 0.6261,
      "max": 0.0031920626236615754
    },
    {
      "distance": 0.6224,
      "breakEvenDistance": 0.6199,
      "min": 0.0031920626236615754,
      "max": 0.003223405873670448
    },
    {
      "distance": 0.6202,
      "breakEvenDistance": 0.6142,
      "min": 0.003223405873670448,
      "max": 0.003253791039488344
    },
    {
      "distance": 0.6174,
      "breakEvenDistance": 0.6081,
      "min": 0.003253791039488344,
      "max": 0.003285709011703031}],


"sell": [
    {
      "distance": 0.8012,
      "breakEvenDistance": 0.8005,
      "max": 0.0024962095663052064
    },
    {
      "distance": 0.7996,
      "breakEvenDistance": 0.7939,
      "min": 0.0024962095663052064,
      "max": 0.002516799325547373
    },
    {
      "distance": 0.794,
      "breakEvenDistance": 0.7877,
      "min": 0.002516799325547373,
      "max": 0.0025370182220432014
    },
    {
      "distance": 0.7927,
      "breakEvenDistance": 0.7807,
      "min": 0.0025370182220432014,
      "max": 0.0025605480833123294
    }]

我知道有一个功能pd.DataFrame.to_json，但是它适用于一个数据帧，关于如何使用上述格式的2个数据帧有任何线索吗？我必须合并它们吗？ buy面是df_gammask，而sell面是dg_gammabid！谢谢

Answer 1

在嵌套字典理解中使用DataFrame.to_dict来删除丢失的值，然后创建a, b, c并转换为dictionary：

json

import json
L1 = [{k: v for k, v in x.items() if pd.notnull(v)} for x in df_gammask.to_dict('r')]
L2 = [{k: v for k, v in x.items() if pd.notnull(v)} for x in df_gammabid.to_dict('r')]

Answer 2

Firs将您的数据框转换为字典：

dict_gammask = df_gammask.to_dict()
dict_gammabid = df_gammabid.to_dict()

然后将它们放在所需结构的另一本词典中：

result_dict = {'buy': dict_gammabid, 'sell': dict_gammask}

然后您可以将其转换为json：

import json
json_result = json.dumps(result_dict)

或将其保存到文件中

with open('data.json', 'w') as outfile:
    json.dump(result_dict, outfile)

使用Pandas将两个不同的数据帧转换为一个json文件

2 个答案: