def spliter(NUM):
  lst = []
  lst.append(int(NUM*0.8))
  lst.append(int(NUM*0.1))
  lst.append(int(NUM*0.1))
  turn = 2
  while(lst[0]+lst[1]+lst[2] != NUM):
    lst[turn] = lst[turn] + 1
    if turn == 0:
      turn = 1
    elif turn == 1:
      turn = 2
    elif turn == 2:
      turn = 0
  return(lst)

print(spliter(23))

输出：

[18, 2, 3]

如果这是你的 Dataframe ：

import pandas as pd
data = {
    'Column A' : [1000,2000,4000,7000,3000],
    'Column B'  : [23,50,20,70,64]
}
df1 = pd.DataFrame(data)
print(df1)

输出：

Column A  Column B
0      1000        23
1      2000        50
2      4000        20
3      7000        70
4      3000        64

我们可以通过以下方式获得所需的 Dataframe ：

df2 = [[],[],[]]
for index,row in df1.iterrows():
  lst = spliter(df1['Column B'][index])
  for i in range(1,lst[0]+1):
    df2[0].append(df1['Column A'][index])
    df2[1].append(i)
    df2[2].append('Train')
  for i in range(1,lst[1]+1):
    df2[0].append(df1['Column A'][index])
    df2[1].append(i)
    df2[2].append('Test')
  for i in range(1,lst[2]+1):
    df2[0].append(df1['Column A'][index])
    df2[1].append(i)
    df2[2].append('Val')

df3 = pd.DataFrame(columns = ['Column A','Column B','Column C'])
df3['Column A'] = df2[0]
df3['Column B'] = df2[1]
df3['Column C'] = df2[2]
print(df3)

输出：

Column A  Column B Column C
0        1000         1    Train
1        1000         2    Train
2        1000         3    Train
3        1000         4    Train
4        1000         5    Train
..        ...       ...      ...
222      3000         3      Val
223      3000         4      Val
224      3000         5      Val
225      3000         6      Val
226      3000         7      Val

[227 rows x 3 columns]