Write and read pandas dataframes with multiindex columns

I am trying to save and load a pandas DataFrame including MultiIndex (2 levels of indexing) for the columns. I have issues to save and load the DataFrame (I want to have exactly the same dataframe when I reload it if possible)

My dataframe looks like this:

> df.head()
         A                   B
        sp start  end       sp start  end
0  V5894_1   243  251  V5894_1   243  251
1  V5894_1   244  252  V5894_1   244  252
2  V5894_1   244  252  V5894_1   244  252
3  V3246_0    28   36  V3246_0    28   36
4  V3246_0    29   37  V3246_0    29   37

What I tried for now is the regular df.to_csv("test.csv") and load it after with df.read_csv("test.csv",index_col=[0,1]).

When I save it, the .csv files looks like this:

,A,A,A,B,B,B
,sp,start,end,sp,start,end
0,V5894_1,243,251,V5894_1,243,251
1,V5894_1,244,252,V5894_1,244,252
2,V5894_1,244,252,V5894_1,244,252
3,V3246_0,28,36,V3246_0,28,36

So I already feel like the structure might already be a bit broken.

When I load it with the previous command, I get:

                   A.1  A.2        B    B.1  B.2
        A
NaN     sp       start  end       sp  start  end
0.0     V5894_1    243  251  V5894_1    243  251
1.0     V5894_1    244  252  V5894_1    244  252
2.0     V5894_1    244  252  V5894_1    244  252
3.0     V3246_0     28   36  V3246_0     28   36

As you can see, I lost my MultiIndex column structure.

I also tried to load with

pd.read_csv("test.csv",index_col=0)

But I still don't get the expect result:

           A    A.1  A.2        B    B.1  B.2
NaN       sp  start  end       sp  start  end
0.0  V5894_1    243  251  V5894_1    243  251
1.0  V5894_1    244  252  V5894_1    244  252
2.0  V5894_1    244  252  V5894_1    244  252
3.0  V3246_0     28   36  V3246_0     28   36

My questions are:

• Is there a way to save and load simply?

• If not, what is the best way to restore the structure I had previously