熊猫1.1.4
再次:
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
Run Code Online (Sandbox Code Playgroud)
想把它打造成
view click
Code type
1 A 3000 3
2 A 2300 23
1 B 1200 5
2 B 300 3
Run Code Online (Sandbox Code Playgroud)
我可以做到,但想探索更多(干净)的选择。
我的索尔
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])
Run Code Online (Sandbox Code Playgroud)
但代码很脏。
Shu*_*rma 12
这本质上是一个重塑操作stack
df.columns = df.columns.str.split('_', expand=True)
df.stack().rename_axis(['code', 'type'])
Run Code Online (Sandbox Code Playgroud)
click view
code type
1 A 3 3000
B 5 1200
2 A 23 2300
B 3 300
Run Code Online (Sandbox Code Playgroud)
尝试与pd.wide_to_long
out = pd.wide_to_long(df.reset_index(),
['view','click'],
i='Code',
j='type',
sep='_',
suffix='\\w+')
view click
Code type
1 A 3000 3
2 A 2300 23
1 B 1200 5
2 B 300 3
Run Code Online (Sandbox Code Playgroud)