Hierarchical indexing

In the index of the Series, Tens is level 0 and Ones is level 1. Ones is the last or innermost level of the index.

import sys
import pandas as pd

nrows = 3
ncols = 4
rangeOfRows = range(10, 10 * (nrows + 1), 10) #count by 10s
rangeOfCols = range(1, ncols + 1)             #count by 1s

index = [
    [row for row in rangeOfRows for _ in rangeOfCols],
    nrows * list(rangeOfCols)
]

data = [tens + ones for tens, ones in zip(*index)]

series = pd.Series(data = data, index = index, name = "Sums")
series.index.names = ["Tens", "Ones"]
print(series)
print()

df = series.unstack()
print(df)
print()

series = df.stack()
print(series)

sys.exit(0)

Tens  Ones
10    1       11
      2       12
      3       13
      4       14
20    1       21
      2       22
      3       23
      4       24
30    1       31
      2       32
      3       33
      4       34
Name: Sums, dtype: int64

Ones   1   2   3   4
Tens                
10    11  12  13  14
20    21  22  23  24
30    31  32  33  34

Tens  Ones
10    1       11
      2       12
      3       13
      4       14
20    1       21
      2       22
      3       23
      4       24
30    1       31
      2       32
      3       33
      4       34
dtype: int64

import sys
import string
import functools
import numpy as np
import pandas as pd
import roman_numerals

levels = [
    ["Romans",  2],
    ["Letters", 2],  #how many letters per Roman numeral
    ["Numbers", 2]   #how many numbers per letter
]

nRomans  = levels[0][1]
nLetters = levels[1][1]   #letters per roman
nNumbers = levels[2][1]   #numbers per letter

romans = [
    roman_numerals.convert_to_numeral(i)
    for i in range(1, nRomans + 1)
    for j in range(nLetters)
    for k in range(nNumbers)
]

letters = [
    letter
    for i in range(1, nRomans + 1)
    for letter in string.ascii_uppercase[:nLetters]
    for k in range(nNumbers)
]

numbers = [
    number
    for i in range(1, nRomans + 1)
    for j in range(nLetters)
    for number in list(range(1, nNumbers + 1))
]

listOfLists = [
    romans,
    letters,
    numbers
]

names =  [level[0] for level in levels]
counts = [level[1] for level in levels]
nRows = functools.reduce(lambda product, factor: product * factor, counts, 1)

multiIndex = pd.MultiIndex.from_arrays(listOfLists, names = names)

series = pd.Series(
    data = np.arange(nRows),
    index = multiIndex,
    name = "Outline"
)

print(series)
sys.exit(0)

Romans  Letters  Numbers
Ⅰ       A        1          0
                 2          1
        B        1          2
                 2          3
Ⅱ       A        1          4
                 2          5
        B        1          6
                 2          7
Name: Outline, dtype: int64