参考数据：

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

      view_A    times_A     view_B  times_B
Code            
1     3000        3          1200      5
2     2300       23          300       3

实现结果：

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

1、使用stack()实现

相关文档：Python pandas.DataFrame.stack函数方法的使用

import pandas as pd
df = pd.DataFrame({"Code":[1,2], "view_A":[3000, 2300], "times_A":[3, 23], 
                   "view_B":[1200, 300], "times_B":[5, 3]})
df.columns = df.columns.str.split('_', expand=True)
print(df.stack().rename_axis(['code', 'type']))

输出：

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

2、使用wide_to_long()实现

import pandas as pd
df = pd.DataFrame({"Code":[1,2], "view_A":[3000, 2300], "times_A":[3, 23], "view_B":[1200, 300], "times_B":[5, 3]})
print(pd.wide_to_long(df.reset_index(),
                      ['view','times'],
                      i='Code',
                      j='type',
                      sep='_',
                      suffix='\\w+'))

输出：

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

3、使用pivot_longer()实现

# pip install pyjanitor
import pandas as pd
import janitor
df = pd.DataFrame({"Code":[1,2], "view_A":[3000, 2300], "times_A":[3, 23], 
                   "view_B":[1200, 300], "times_B":[5, 3]})
print(df.pivot_longer(index='Code', 
                 names_to=('.value', 'type'), 
                 names_sep='_')
   .set_index(['Code', 'type'])
)

输出：

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