python 实现rolling和apply函数的向下取值操作

import pandas as pd

def get_under_rolling(df,window,user,name):
  df[name] = df[user].iloc[::-1].rolling(window=window).apply(lambda x:x[0]).iloc[::-1]
  return df

if __name__ == '__main__':
  df = pd.DataFrame({'a':[1,2,3,4,5],
          'b':[2,3,4,5,6]})
  # 把b列向下取值作为新的c列
  df = get_under_rolling(df, window=3, user='b',name='c')

# 设置一个初始数据框
df1 = [1,2,3,4,5]
df2 = [2,3,4,5,6]
df = pd.DataFrame({'a':list(df1),'b':list(df2)})
print(df)

  a b
 0 1 2
 1 2 3
 2 3 4
 3 4 5
 4 5 6

# 多列滚动函数
# handle对滚动的数据框进行处理
def handle(x,df,name,n):
  df = df[name].iloc[x:x+n,:]
  print(df)
  return 1
# group_rolling 进行滚动 
# n：滚动的行数
# df：目标数据框
# name：要滚动的列名
def group_rolling(n,df,name):
  df_roll = pd.DataFrame({'a':list(range(len(df)-n+1))})
  df_roll['a'].rolling(window=1).apply(lambda x:handle(int(x[0]),df,name,n),raw=True)

  a b
0 1 2
1 2 3

  a b
1 2 3
2 3 4

  a b
2 3 4
3 4 5

  a b
3 4 5
4 5 6