python中的拆分列标题编号和字符串

Question

下面是我的玩具示例，我的问题是如何创建名为trial={2,3}的新列，2&3来自2.0__sum_values，3.0__sum_values列中的数字部分，

我的代码是：

import pandas as pd

before_spliting = {"ID": [1, 2,3], "2.0__sum_values": [33,28,40],"2.0__mediane": [33,70,20],"2.0__root_mean_square":[33,4,30],"3.0__sum_values": [33,28,40],"3.0__mediane": [33,70,20],"3.0__root_mean_square":[33,4,30]}
before_spliting = pd.DataFrame(before_spliting)
print(before_spliting)

   ID  2.0__sum_values  2.0__mediane  2.0__root_mean_square  3.0__sum_values  \
0   1               33            33                     33               33   
1   2               28            70                      4               28   
2   3               40            20                     30               40   

   3.0__mediane  3.0__root_mean_square  
0            33                     33  
1            70                      4  
2            20                     30  


after_spliting = { "ID": [1,1,2, 2,3,3], "trial": [2, 3,2,3,2,3],"sum_values": [33,33,28,28,40,40],"mediane": [33,33,70,70,20,20],"root_mean_square":[33,33,4,4,30,30]}
after_spliting = pd.DataFrame(after_spliting)
print(after_spliting)

   ID  trial  sum_values  mediane  root_mean_square
0   1      2          33       33                33
1   1      3          33       33                33
2   2      2          28       70                 4
3   2      3          28       70                 4
4   3      2          40       20                30
5   3      3          40       20                30

Answer 1

你可以试试：

res = df.melt(id_vars="ID")
res[["trial", "columns"]] = res["variable"].str.split("__", expand=True)
res = (
    res
    .pivot_table(
        index=["ID", "trial"], columns="columns", values="value", aggfunc=list
    )
    .explode(sorted(set(res["columns"])))
    .reset_index()
)

以下输入数据的结果

data = {
    "ID": [1, 2, 3],
    "2.0__sum_values": [33, 28, 40], "2.0__mediane": [43, 80, 30], "2.0__root_mean_square":[37, 4, 39],
    "3.0__sum_values": [34, 29, 41], "3.0__mediane": [44, 81, 31], "3.0__root_mean_square":[38, 5, 40]
}
df = pd.DataFrame(data)

是

columns  ID trial mediane root_mean_square sum_values
0         1   2.0      43               37         33
1         1   3.0      44               38         34
2         2   2.0      80                4         28
3         2   3.0      81                5         29
4         3   2.0      30               39         40
5         3   3.0      31               40         41

具有相同输出的替代解决方案：

res = df.melt(id_vars="ID")
res[["trial", "columns"]] = res["variable"].str.split("__", expand=True)
res = res.set_index(["ID", "trial"]).drop(columns="variable").sort_index()
res = pd.concat(
    (group[["value"]].rename(columns={"value": key})
     for key, group in res.groupby("columns")),
    axis=1
).reset_index()

Answer 2

因为您使用的是花括号{}，所以在花括号{}中不可能有重复的变量，因此可以使用方括号[]来创建新列。

trial = []
for i in range(len(d1)):
    trial.append([d1['2.0__sum_values'][i], d1['3.0__sum_values'][i]])

d1['trial'] = trial

最好的运气