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pythonpandaspivottransposemelt

Pandas: pivoting rows to columns with columns as column-row

I have a data frame that looks like this 

df = pd.DataFrame({'A': [1,2,3], 'B': [11,12,13]})
df

    A   B
0   1   11
1   2   12
2   3   13

I would like to create the following data frame where the columns are a combination of each column-row

    A0  A1  A2  B0  B1  B2
0   1   2   3   11  12  13

It seems that the pivot and transpose functions will switch columns and rows but I actually want to flatten the data frame to a single row. How can I achieve this?

Solution

  • IIUC

    s=df.stack().sort_index(level=1).to_frame(0).T
s.columns=s.columns.map('{0[1]}{0[0]}'.format) 
s
   A0  A1  A2  B0  B1  B2
0   1   2   3  11  12  13