Connecting a dataframe and another 1d dataframe isn't a problem, but when using the […] operator it yields different results

I have an original dataframe og_df and a sublist dataframe, which is a part of the og_df. I want to create a new dataframe new_df which contains the elements of og_df and every n following elements in the og_df.
Example:

og_df = pd.DataFrame({'column': range(20)})
sub_df = pd.DataFrame({'column': [ 1, 2, 10 ]})
n = 3  
new_df = pd.DataFrame({'column':[]})

for index in sub_df.index:
    new_df = pd.concat([new_frame, og_df.iloc[index:index + n]])
print(new_df)

>>>    column
    0    1
    1    2
    2    3
    1    2
    2    3
    3    4
    11   10
    12   11
    13   12

This worked the way I wanted and gives the desired result. However, when og_df has multiple columns and I use the [..] operator, or if it has one column and I use the [..] operator it does behave like this:

for index in sub_df.index:
    new_df = pd.concat([new_frame, og_df['column'].iloc[index:index + n]])
print(new_df)

>>>    column     0
1      NaN   1.0
2      NaN   2.0
3      NaN   3.0
2      NaN   2.0
3      NaN   3.0
4      NaN   4.0
10     NaN  10.0
11     NaN  11.0
12     NaN  12.0

How can I make it behave like desired? I aim to select just one column from a multicolumn og_df and that’s the reason i’m using the [..] operator.

>Solution :

The issue you’re facing is that you’re using a single slice [] instead of double slice [[]].

If you update your loop the code works:

new_df = pd.DataFrame({'column':[]})
for index in sub_df.index:
    new_df = pd.concat([new_df, og_df[['column']].iloc[index:index + n]])
print(new_df)

Output:

   column
0     0.0
1     1.0
2     2.0
1     1.0
2     2.0
3     3.0
2     2.0
3     3.0
4     4.0

This happens because a single slice gives a series:

type(og_df['column']), type(og_df[['column']])

(pandas.core.series.Series, pandas.core.frame.DataFrame)