I've a sample pivoted data using pandas pivot_table()
df = pd.DataFrame([['USA', 'LA', 'April', 2, '1:2'],
                           ['USA', 'FL', 'April', 5, '5:6'],
                           ['USA', 'TX', 'April', 7, '1:3'],
                           ['Canada', 'Ontario', 'April', 2, '1:3'],
                           ['Canada', 'Toronto', 'April', 3, '1:5'],
                           ['USA', 'LA', 'May', 3, '4:5'],
                           ['USA', 'FL', 'May', 6, '4:5'],
                           ['USA', 'TX', 'May', 2, '1:4'],
                           ['Canada', 'Ontario', 'May', 6, '8:9'],
                           ['Canada', 'Toronto', 'May', 9, '3:4']],
             columns=['Country', 'Cities', 'month', 'Count', 'Ratio'])
mux1 = pd.MultiIndex.from_product([data['month'].unique(), ['Count', 'Ratio']])
data = data.pivot_table(columns=['month'], values=['Count', 'Ratio'], index=['Country', 'Cities']).swaplevel(1, 0, axis=1).reindex(mux1, axis=1)
                                April              May
                         Count      Ratio    Count   Ratio
 Country    Cities
   USA       LA           2          1:2      3       4:5
             FL           5          5:6      6       4:5
             TX           7          1:3      2       1:4
   Canada    Ontario      2          1:3      6       8:9
             Toronto      3          1:5      9       3:4
How could I repeat my row labels in the pivot data which looks like below and export it as excel?
                                April              May
                         Count      Ratio    Count   Ratio
 Country    Cities
   USA        LA           2         1:2       3      4:5
   USA        FL           5         5:6       6      4:5
   USA        TX           7         1:3       2      1:4
   Canada     Ontario      2         1:3       6      8:9
   Canada     Toronto      3         1:5       9      3:4
I've tried pd.option_context('display.multi_sparse', False), as it only display the content, it does not export data as excel.
 
     
    