Python 如何训练每一个pandaprame行的线性回归并生成斜率

我制作了以下的Pandas pandas p

import numpy as np
import pandas as pd
    
ds = {'col1' : [11,22,33,24,15,6,7,68,79,10,161,12,113,147,115]}
df = pd.DataFrame(data=ds)

predFeature = []

for i in range(len(df)):
    predFeature.append(0)
    predFeature[i] = predFeature[i-1]+1

df['predFeature'] = predFeature

                
arrayTarget = []
arrayPred = []
target = np.array(df['col1'])
predFeature = np.array(df['predFeature'])

for i in range(len(df)):

    arrayTarget.append(target[i-4:i])
    arrayPred.append(predFeature[i-4:i])
        
df['arrayTarget'] = arrayTarget
df['arrayPred'] = arrayPred

它看起来像这样:

    col1  predFeature          arrayTarget         arrayPred
0     11            1                   []                []
1     22            2                   []                []
2     33            3                   []                []
3     24            4                   []                []
4     15            5     [11, 22, 33, 24]      [1, 2, 3, 4]
5      6            6     [22, 33, 24, 15]      [2, 3, 4, 5]
6      7            7      [33, 24, 15, 6]      [3, 4, 5, 6]
7     68            8       [24, 15, 6, 7]      [4, 5, 6, 7]
8     79            9       [15, 6, 7, 68]      [5, 6, 7, 8]
9     10           10       [6, 7, 68, 79]      [6, 7, 8, 9]
10   161           11      [7, 68, 79, 10]     [7, 8, 9, 10]
11    12           12    [68, 79, 10, 161]    [8, 9, 10, 11]
12   113           13    [79, 10, 161, 12]   [9, 10, 11, 12]
13   147           14   [10, 161, 12, 113]  [10, 11, 12, 13]
14   115           15  [161, 12, 113, 147]  [11, 12, 13, 14]

我需要生成一个名为slope的新列，它对应于为每行训练的线性回归系数，并针对该系数:

• target =每个数组包含在arrayTarget
• 预测功能=arrayPred中包含的每个数组

例如:

• 前4行的slope是null.

• 第5行的斜率由考虑以下值的线性回归系数给出:

  • 独立值(或预测值):[1, 2, 3, 4]
  • 相关值(或预测值):[11, 22, 33, 24] 结果是:0.10204081632653061.

• 第6行的斜率由考虑以下值的线性回归系数给出:

  • 独立值(或预测值):[2, 3, 4, 5]
  • 相关值(或预测值):[22, 33, 24, 15] 结果是:-0.09090909090909091.

等

有谁能帮帮我吗？