Convert subset of columns to rows by combining columns

Pandas 1.1.4

MRE:

df = pd.DataFrame({"Code":[1,2], "view_A":[3000, 2300], "click_A":[3, 23], 
                   "view_B":[1200, 300], "click_B":[5, 3]})
df.set_index("Code", inplace=True)

>>>
      view_A    click_A     view_B  click_B
Code            
1     3000        3          1200      5
2     2300       23          300       3

Want to make it into

              view      click
Code  type 
 1     A      3000        3
 2     A      2300       23
 1     B      1200        5
 2     B      300         3

I can do it, but want to explore more (clean) options.

My sol’tn

a_df = df[["view_A", "click_A"]].rename(columns={"view_A":"view", "click_A":"click"})
a_df["type"] = "A"

b_df = df[["view_B", "click_B"]].rename(columns={"view_B":"view", "click_B":"click"})
b_df["type"] = "B"
final_df = pd.concat([a_df, b_df])

But code is dirty.

Answer

This is essentially a reshape operation using stack

df.columns = df.columns.str.split('_', expand=True)
df.stack().rename_axis(['code', 'type'])

---

           click  view
code type             
1    A         3  3000
     B         5  1200
2    A        23  2300
     B         3   300