将带子集的 table 转换为 Json 格式

Question

我正在尝试处理上市公司的财务信息。我已经下载了数据，现在我正在尝试将其转换为 JSON 格式。

table中有小节，使用 4 ~ 表示 1 个缩进，8 表示 2 个缩进，如下所示：

一个缩进表示向下一级
双缩进表示向下 2 级

例如 Cost of Goods Sold (COGS) incl. D&A 是部分 header 并且 COGS Growth 应该被捕获为Cost of Goods Sold (COGS) incl. D&A.

的 child 元素

能否请您帮我确定一种将此数据框转换为 JSON 文件的方法？

Table表示数据帧

|                                       Item  Item|      2016|     2017 |    2018 |    2019   |     2020 |  5-year trend|
|                                     :---------: |    :----:|   :----: |  :----: |  :----:   |   :----: |:------------:|
| Sales/Revenue                                   |-         |-         |-        | -         |615.82K   | NaN          |
| ~~~~Sales Growth                                |-         |-         |-        | -         |-         | NaN          |
| Cost of Goods Sold (COGS) incl. D&A             |684       |5.44K     |3.14K    | 32.5K     |-         | NaN          |
| ~~~~COGS Growth                                 |-         |694.59%   |-42.19%  | 934.31%   |-         | NaN          |
| ~~~~COGS excluding D&A                          |-         |-         |-        | -         |-         | NaN          |
| ~~~~Depreciation & Amortization Expense         |684       |5.44K     |3.14K    | 32.5K     |41.83K    | NaN          |
| ~~~~~~~~Depreciation                            |684       |5.44K     |3.14K    | 32.5K     |41.83K    | NaN          |
| ~~~~~~~~Amortization of Intangibles             |-         |-         |-        | -         |-         | NaN          |
| Gross Income                                    |(684)     |(5.44K)   |(3.14K)  | (32.5K)   |-         | NaN          |
| ~~~~Gross Income Growth                         |-         |-694.59%  |42.19%   | -934.31%  |-         | NaN          |
| ~~~~Gross Profit Margin                         |-         |-         |-        | -         |-         | NaN          |
| SG&A Expense                                    |1.91M     |4.79M     |5.88M    | 9.5M      |9.63M     | NaN          |
| ~~~~SGA Growth                                  |-         |151.12%   |22.61%   | 61.51%    |1.37%     | NaN          |
| ~~~~Research & Development                      |-         |-         |-        | -         |-         | NaN          |
| ~~~~Other SG&A                                  |1.91M     |4.79M     |5.88M    | 9.5M      |9.63M     | NaN          |
| ~~~~Other Operating Expense                     |-         |-         |-        | -         |-         | NaN          |
| Unusual Expense                                 |-         |-         |-        | -         |-         | NaN          |
| EBIT after Unusual Expense                      |-         |-         |-        | -         |-         | NaN          |
| Non Operating Income/Expense                    |-         |-         |(52.76K) | 60.09K    |(2.2K)    | NaN          |
| Non-Operating Interest Income                   |8.9K      |170.93K   |59.8K    | 50.79K    |19.15K    | NaN          |
| Equity in Affiliates (Pretax)                   |-         |-         |-        | -         |-         | NaN          |
| Interest Expense                                |-         |-         |-        | -         |115.55K   | NaN          |
| ~~~~Interest Expense Growth                     |-         |-         |-        | -         |-         | NaN          |
| ~~~~Gross Interest Expense                      |-         |-         |-        | -         |115.55K   | NaN          |
| ~~~~Interest Capitalized                        |-         |-         |-        | -         |-         | NaN          |

Table 分小节组织

Item Item	Subsection1	Subsection2	2016	2017	2018	2019	2020	5-year trend
Sales/Revenue			-	-	-	-	615.82K	NaN
	Sales Growth		-	-	-	-	-	NaN
Cost of Goods Sold (COGS) incl. D&A			684	5.44K	3.14K	32.5K	-	NaN
	COGS Growth		-	694.59%	-42.19%	934.31%	-	NaN
	COGS excluding D&A		-	-	-	-	-	NaN
	Depreciation & Amortization Expense		684	5.44K	3.14K	32.5K	41.83K	NaN
		Depreciation	684	5.44K	3.14K	32.5K	41.83K	NaN
		Amortization of Intangibles	-	-	-	-	-	NaN
Gross Income			(684)	(5.44K)	(3.14K)	(32.5K)	-	NaN
	Gross Income Growth		-	-694.59%	42.19%	-934.31%	-	NaN
	Gross Profit Mar		-	-	-	-	-	NaN
SG&A Expense			1.91M	4.79M	5.88M	9.5M	9.63M	NaN
	SGA Growth		-	151.12%	22.61%	61.51%	1.37%	NaN
	Research & Development		-	-	-	-	-	NaN
	Other SG&A		1.91M	4.79M	5.88M	9.5M	9.63M	NaN
	Other Operating Expense		-	-	-	-	-	NaN
Unusual Expense			-	-	-	-	-	NaN
EBIT after Unusual Expense			-	-	-	-	-	NaN
Non Operating Income/Expense			-	-	(52.76K)	60.09K	(2.2K)	NaN
Non-Operating Interest Income			8.9K	170.93K	59.8K	50.79K	19.15K	NaN
Equity in Affiliates (Pretax)			-	-	-	-	-	NaN
Interest Expense			-	-	-	-	115.55K	NaN
	Interest Expense Growth		-	-	-	-	-	NaN
	Gross Interest Expense		-	-	-	-	115.55K	NaN
	Interest Capitalized		-	-	-	-	-	NaN

Answer 1

我可以通过向缺失的单元格添加值然后对 3 列进行分组来解决此问题，代码如下所示。这是我用来构建此代码的

d = (dframe.fillna("-").groupby(['Item  Item','ItemSubsection1','ItemSubsection2'])['2016','2017','2018','2019','2020']
       .apply(lambda x: x.to_dict('r'))
       .reset_index(name='data')
       .groupby(['Item  Item','ItemSubsection1'])['ItemSubsection2','data']
       .apply(lambda x: x.to_dict('r'))
       .reset_index(name='data')
       .groupby('Item  Item')['ItemSubsection1','data']
       .apply(lambda x: x.set_index('ItemSubsection1', 'ItemSubsection2')['data'].to_dict())
       .to_json()
       )

将带子集的 table 转换为 Json 格式

Convert a table with subset to a Json format

python

formatting

json

python-3.x

pandas