Python Pandas:使用切片作为变量的表操作 [英] Python Pandas: Table manipulation with slices as variables

问题描述

我有一张如下表(黑色).我想在右侧创建一个额外的列，例如以红色显示.基本上，对于切片"列中的每个切片变量，我都希望从低"列中检索相应的值.

I have a table such as follow (in black). I would like to create an additional column such as visible in red, to the right. Basically for each slice variable in the "slice" column, I want retrieve the corresponding values from the "low" column.

我尝试了无数种方法，我已经在这里发布了一个问题，试图解决我可能会使用的一种方法:

I have tried countless ways of doing that, I already posted a question here trying to address one of the approach i though would work:

Python Pandas:与Pandas一起使用时，该功能不起作用apply()

该问题的一位答复者建议我简单地询问如何实现它，因此我就在这里.

One of the respondents to that question suggested that i simply ask how to achieve it, hence here I am.

我还重新发布了下面的代码以重建该数据框:

I also repost below the code to reconstruct that dataframe:

df = pd.DataFrame(dict, columns=["low", "slices"])

  {'low': {0: 1207.25,
  1: 1207.5,
  2: 1205.75,
  3: 1206.0,
  4: 1201.0,
  5: 1202.75,
  6: 1203.75},
 'slices': {0: [slice(1, 1, None)],
  1: [slice(1, 2, None), slice(2, 2, None)],
  2: [slice(1, 3, None), slice(2, 3, None), slice(3, 3, None)],
  3: [slice(1, 4, None),
   slice(2, 4, None),
   slice(3, 4, None),
   slice(4, 4, None)],
  4: [slice(1, 5, None),
   slice(2, 5, None),
   slice(3, 5, None),
   slice(4, 5, None),
   slice(5, 5, None)],
  5: [slice(1, 6, None),
   slice(2, 6, None),
   slice(3, 6, None),
   slice(4, 6, None),
   slice(5, 6, None),
   slice(6, 6, None)],
  6: [slice(1, 7, None),
   slice(2, 7, None),
   slice(3, 7, None),
   slice(4, 7, None),
   slice(5, 7, None),
   slice(6, 7, None),
   slice(7, 7, None)]}}

推荐答案

以这种方式定义函数

def fun(slices):
    return [df.low.loc[s].tolist() for s in slices]

并应用于切片"列

df['slices_low'] = df.slices.apply(fun)

df

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