How do I write this as a single for loop?

Question

I have to split the data into four groups and each split data into groups and subgroups like the following. How do I write this as a single for loop?

What I tried so far?

df = pd.DataFrame({'Data':[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]})

n = round(len(df)/4)


groups = [df[i:i+n] for i in range(0,df.shape[0],n)]

first_group = groups[0]
second_group = groups[1]
third_group = groups[2]
fourth_group = groups[3]


split1 = first_group.copy().reset_index(drop=True)
split1['Group'] = 'A'
split1['Sub group'] = pd.Series(range(101, 105))

split2 = second_group.copy().reset_index(drop=True)
split2['Group'] = 'B'
split2['Sub group'] = pd.Series(range(201, 205))

split3 = third_group.copy().reset_index(drop=True)
split3['Group'] = 'C'
split3['Sub group'] = pd.Series(range(301, 305))

split4 = fourth_group.copy().reset_index(drop=True)
split4['Group'] = 'D'
split4['Sub group'] = pd.Series(range(401, 405))

n_split = pd.concat([split1, split2, split3, split4])

Output should look something like the following table:

  Data Group Sub group
0   1   A   101
1   2   A   102
2   3   A   103
3   4   A   104
0   5   B   201
1   6   B   202
2   7   B   203
3   8   B   204
0   9   C   301
1   10  C   302
2   11  C   303
3   12  C   304
0   13  D   401
1   14  D   402
2   15  D   403
3   16  D   404

Answer 1

no need for loops here.

we can use map and cumcount

personally, i would set 4 as a constant variable so you play around with the divmod of your index to make it totally dynamic.

import pandas as pd
from string import ascii_uppercase 

df = pd.DataFrame({'Data':[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]})
idx = set(df.index // 4)


df['group'] = (df.index // 4).map(dict(zip(idx, ascii_uppercase )))
df['subgroups'] = (((df.index // 4) + 1) * 100) + df.groupby('group').cumcount() + 1

---

print(df)


   Data group  subgroups
0      1     A        101
1      2     A        102
2      3     A        103
3      4     A        104
4      5     B        201
5      6     B        202
6      7     B        203
7      8     B        204
8      9     C        301
9     10     C        302
10    11     C        303
11    12     C        304
12    13     D        401
13    14     D        402
14    15     D        403
15    16     D        404

Answer 2

Here you go: ord method allows you to loop through the letters (be aware of the limit of course!)

import pandas as pd

df = pd.DataFrame({'Data':[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]})

group_ord = ord('A')
sub_num = 101
groups_list = []
sub_group_list = []
for i, row in df.iterrows():
    groups_list.append(chr(group_ord))
    sub_group_list.append(sub_num)
    
    if row['Data'] % 4 == 0:
        group_ord += 1
        sub_num += 100 - 3
    else:
        sub_num += 1

df['Groups'] = groups_list
df['Sub-groups'] = sub_group_list

df

    Data    Groups  Sub-groups
0   1       A       101
1   2       A       102
2   3       A       103
3   4       A       104
4   5       B       201
5   6       B       202
6   7       B       203
7   8       B       204
8   9       C       301
9   10      C       302
10  11      C       303
11  12      C       304
12  13      D       401
13  14      D       402
14  15      D       403
15  16      D       404