Pandas 如何将系列列表转换为两列数据帧？

我有以下系列的清单

[LVH = 0    63 (88.73 %)
 LVH = 1      6 (8.45 %)
 LVH = 2      1 (1.41 %)
 LVH = 3      1 (1.41 %)
 dtype: object, LV diastolic dysfunction (guideline) = 0    60 (84.51 %)
 LV diastolic dysfunction (guideline) = 1     8 (11.27 %)
 LV diastolic dysfunction (guideline) = 4      3 (4.23 %)
 dtype: object, LV diastolic dysfunction grade (formula) = 0.0    60 (84.51 %)
 LV diastolic dysfunction grade (formula) = 1.0      4 (5.63 %)
 LV diastolic dysfunction grade (formula) = 3.0      4 (5.63 %)
 LV diastolic dysfunction grade (formula) = 4.0      3 (4.23 %)
 dtype: object, LV filling pressure(formula) = 0    67 (94.37 %)
 LV filling pressure(formula) = 1      4 (5.63 %)
 dtype: object, cause of hospitalization = 8      2 (2.82 %)
 cause of hospitalization = 1    43 (60.56 %)
 cause of hospitalization = 2    21 (29.58 %)
 cause of hospitalization = 3      1 (1.41 %)
 cause of hospitalization = 6      4 (5.63 %)
 dtype: object, simplfied cause of hospitalization = 1    43 (60.56 %)
 simplfied cause of hospitalization = 2    22 (30.99 %)
 simplfied cause of hospitalization = 3      4 (5.63 %)
 simplfied cause of hospitalization = 5      2 (2.82 %)
 dtype: object, ACC/AHA = A    10 (14.08 %)
 ACC/AHA = 0    56 (78.87 %)
 ACC/AHA = C      2 (2.82 %)
 ACC/AHA = B      3 (4.23 %)
 dtype: object, ACC-AHA -binary = 0    69 (97.18 %)
 ACC-AHA -binary = 1      2 (2.82 %)
 dtype: object, NYHA = I      65 (91.55 %)
 NYHA = II       2 (2.82 %)
 NYHA = III      4 (5.63 %)
 dtype: object, NYHA-binary = 0    66 (92.96 %)
 NYHA-binary = 1      5 (7.04 %)
 dtype: object]

对于列表的每个元素，即序列，我需要将它们转换为具有两列的数据帧。例如，它应该如下所示：

Column 1                                      Column 2
LVH = 0                                       63 (88.73 %)
LVH = 1                                        6 (8.45 %)
LVH = 2                                        1 (1.41 %)    
LVH = 3                                        1 (1.41 %)
LV diastolic dysfunction (guideline) = 0      60 (84.51 %)
LV diastolic dysfunction (guideline) = 1       8 (84.51 %)
LV diastolic dysfunction (guideline) = 4       3 (84.51 %)
... 

等等。然后将转换为CSV格式供人们下载。我只使用了基本的pd.DataFrame和pd.DataFrame.from_项。第一个将其转换为dataframe，但不是我想要的方式。第二个给出了错误，但我认为这无论如何都不会有帮助。我怎样才能解决这个问题

更新

---

数据是一个数据框，其中包含变量的列名和度量值。数据集庞大而敏感

由于未知数据，我无法复制您的示例，因此我形成了自己的示例。你可以从这里得到帮助-

s1 = pd.Series(['1kg', '2kg'], index=['first', 'second'])
s2 = pd.Series(['3kg', '4kg'], index=['third', 'fourth'])
lst = [s1, s2]
lst

# [first     1kg
#  second    2kg
#  dtype: object, third     3kg
#  fourth    4kg
#  dtype: object]

ndf = pd.concat(lst,  axis = 1, keys=[s.name for s in lst], sort=False).fillna('').apply(lambda x: ''.join(x), axis=1)
ndf = pd.DataFrame(ndf).reset_index()
ndf.columns = ['Column 1', 'Column 2']
ndf


+---+----------+----------+
|   | Column 1 | Column 2 |
+---+----------+----------+
| 0 | first    | 1kg      |
| 1 | second   | 2kg      |
| 2 | third    | 3kg      |
| 3 | fourth   | 4kg      |
+---+----------+----------+

---

给出有问题的代码以生成series@meW，我添加了代码。定义数据too@meW你能详细说明一下吗？数据只是一个数据帧，包含287列和128000行。提供的数据也很敏感。我只对分类数据感兴趣，以了解其分布情况。还有其他几个数据集也有类似的数据。我将为每个数据框运行代码，并将其放入数据框，最终放入excel电子表格，以供用户查看每个数据集组的不同或相似之处，这些数据集组工作正常！！！！非常感谢你！！！我只需要删除sort=False，因为我得到了一个erorr声明pd.concat没有排序函数。我把它拿走了，它成功了。我会进行分类，找出为什么不起作用。

s1 = pd.Series(['1kg', '2kg'], index=['first', 'second'])
s2 = pd.Series(['3kg', '4kg'], index=['third', 'fourth'])
lst = [s1, s2]
lst

# [first     1kg
#  second    2kg
#  dtype: object, third     3kg
#  fourth    4kg
#  dtype: object]

ndf = pd.concat(lst,  axis = 1, keys=[s.name for s in lst], sort=False).fillna('').apply(lambda x: ''.join(x), axis=1)
ndf = pd.DataFrame(ndf).reset_index()
ndf.columns = ['Column 1', 'Column 2']
ndf


+---+----------+----------+
|   | Column 1 | Column 2 |
+---+----------+----------+
| 0 | first    | 1kg      |
| 1 | second   | 2kg      |
| 2 | third    | 3kg      |
| 3 | fourth   | 4kg      |
+---+----------+----------+