Having a df as:
14 15 16
14 10.1166 18.2331 65.0185
15 18.2331 6.664 57.5195
16 65.3499 57.851 20.9907
What is a different more efficient way to modify the df to look as
a b c
0 14 14 10.1166
1 14 15 18.2331
2 14 16 65.0185
3 15 14 18.2331
4 15 15 6.664
etc.
I wrote this code, but i dont like the fact that i need to use a loop for it.
for row in tt.index:
row_vals = tt[tt.index==row]
col_vals = row_vals.T
col_vals['from_zone'] = row
col_vals['to_zone'] = tt.index
col_vals['travel_time'] = col_vals[row].astype('int')
col_vals = col_vals.drop(row, axis=1)
travel_data = pd.concat([travel_data,col_vals])