求个循环！请问如何用pandas将多列合并为单列

Question

 

如题，请问如何将表1 转换为表2？
              cond1 cond2 cond3
emp1        84       74       27
emp2        94        6         31 

  (表1)


Employee Condition         Score
Emp1           Cond1                 84
Emp1           Cond2                 74
Emp1           Cond3                 27
Emp2           Cond1                 94
Emp2           Cond2                 6
Emp2           Cond3                 31

       （表2）
求大佬代码~~感激不尽！

Answer 1

这个需求人看起来不难，但并不好实现，用for循环难免效率太低，下面代码中逐步去生成每一列：

import pandas as pd
from itertools import chain

df1 = pd.DataFrame({"cond1":[84,94], "cond2":[74,6], "cond3":[27,31]}, index=["emp1", "emp2"])
df1_line_num = len(df1)

# 获取行列索引
df1_index = df1.index.tolist()
df1_columns = df1.columns.tolist()

# 构造 Employee 列
Employee = [[item] * len(df1_columns) for item in df1_index]
Employee = list(chain(*Employee))   # 先生成再拍平

# 构造 Condition 列
Condition = df1_columns * len(df1_index)

# 构造 Score 列
Score = df1.values.reshape((-1,)).tolist()

# 生成表2，并大写首字母
df2 = pd.DataFrame({"Employee": Employee, "Condition":Condition, "Score":Score})
df2["Employee"] = df2["Employee"].map(lambda x: x[0].upper()+x[1:])
df2["Condition"] = df2["Condition"].map(lambda x: x[0].upper()+x[1:])

print(df2)

如果有更好的实现欢迎交流哦，希望能帮到你 ^_^