Can sub-columns be created in a pandas data frame?

Question

Data frame

I am working with a data frame in Jupyter Notebooks and I am having some difficulty with it. The data frame consists of locations and these are represented by

Answer 1

To add a top to column to a pd.DataFrame run:

def add_top_column(df, top_col, inplace=False):
    if not inplace:
        df = df.copy()
    
    df.columns = pd.MultiIndex.from_product([[top_col], df.columns])
    return df


orig_df = pd.DataFrame([[1, 2], [3, 4]], columns=['a', 'b'])
new_df = add_top_column(orig_df, "new column")

In order to combine 3 DataFrames each with its own new top column:

new_df2 = add_top_column(orig_df, "new column2")
new_df3 = add_top_column(orig_df, "new column3")
print(pd.concat([new_df, new_df2, new_df3], axis=1))

"""
# And this is the expected output:
  new column    new column2    new column3   
           a  b           a  b           a  b
0          1  2           1  2           1  2
1          3  4           3  4           3  4
"""

Note that if the DataFrames' index do not match, you might need to reset the index.