如何基于问卷回答DataFrame计算各问题的最小受访者年龄

原始数据 #

以下是包含问卷回答的DataFrame：

import pandas as pd
import numpy as np

df = pd.DataFrame(
    data=[
        [10, np.nan, 'Answer 1', 'Answer 2'],
        [40, "Answer 4", "Answer 3", 'Answer 2'],
        [20, "Answer 2", np.nan, 'Answer 1']
    ], 
    columns=['Age', 'Question 1', 'Question 2', 'Question 3']
)

该DataFrame的内容为：

Age Question 1  Question 2  Question 3
0   10  NaN         Answer 1    Answer 2
1   40  Answer 4    Answer 3    Answer 2
2   20  Answer 2    NaN         Answer 1

需求目标 #

生成一个新的DataFrame，记录每个问卷问题对应的受访者最小年龄。

实现代码（注：代码写法较为粗糙） #

df2 = pd.DataFrame(data=df.columns.tolist(), columns=["Questions"])
for col in df2["Questions"]:
    if col != "Age":
        # 过滤掉当前问题无回答的行，再取最小年龄
        df2.loc[df2["Questions"] == col, "min_age"] = df.loc[:, ["Age", col]].dropna()["Age"].min()

最终生成的df2内容为：

Questions    min_age
0   Age         NaN
1   Question 1  20.0
2   Question 2  10.0
3   Question 3  10.0

内容的提问来源于stack exchange，提问作者gabboshow