The

Aesthetics aside, the structure here is very clear, and indeed, the same as the structure in our df. Take notice of the merged cells especially.

Now, let's suppose we want to retrieve this data again from the Excel file at some later point, and we use pd.read_excel with default parameters. Problematically, we will end up with a complete mess:

df = pd.read_excel('file.xlsx')
print(df)

  Unnamed: 0  col_0         A  Unnamed: 3         B  Unnamed: 5
0        NaN  col_1  1.000000    2.000000  1.000000    2.000000
1      idx_0  idx_1       NaN         NaN       NaN         NaN
2          0      1  0.952749    0.447125  0.846409    0.699479
3        NaN      2  0.297437    0.813798  0.396506    0.881103
4          1      1  0.581273    0.881735  0.692532    0.725254
5        NaN      2  0.501324    0.956084  0.643990    0.423855

Getting this data "back into shape" would be quite time-consuming. To avoid such a hassle, we can rely on the parameters index_col and header inside pd.read_excel:

df2 = pd.read_excel('file.xlsx', index_col=[0,1], header=[0,1])

print(df2)
col_0               A                   B          
col_1               1         2         1         2
idx_0 idx_1                                        
0     1      0.952749  0.447125  0.846409  0.699479
      2      0.297437  0.813798  0.396506  0.881103
1     1      0.581273  0.881735  0.692532  0.725254
      2      0.501324  0.956084  0.643990  0.423855

# check for equality
df.equals(df2)
# True

As you can see, we have made a "round trip" here, and index_col and header allow for it to have been smooth sailing!

Two final notes:

1. (minor) The docs for pd.read_excel contain a typo in the index_col section: it should read merge_cells=True, not merged_cells=True.
2. The header section is missing a similar comment (or a reference to the comment at index_col). This is somewhat confusing. As we saw above, the two behave exactly the same (for present purposes, at least).