python - 如何在 Pandas 中添加基于选定行过滤器的列？

Question

你好，我想根据学生目前的分数+他们最喜欢的科目的分数给他们一个最终分数。

import pandas as pd
new_data = [['tom', 31, 50, 30, 20, 'English'], ['nick', 30, 42, 23, 21, 'Math'], ['juli', 39, 14, 40, 38, 'Science']]
df = pd.DataFrame(new_data, columns = ['Name','Current_Score','English','Science','Math','Favourite_Subject'])
for subj in df['Favourite_Subject'].unique():
    mask = (df['Favourite_Subject'] == subj)
    df['Final_Score'] = df[mask].apply(lambda row: row['Current_Score'] + row[subj], axis=1)

    Name    Score   English Science Math    Favourite_Subject   Final_Score
0   tom       31       50    30      20         English          NaN
1   nick      30       42    23      21         Math             NaN
2   juli      39       14    40      38         Science          79.0

当我应用上述函数时，我在“Final_Score”列的其他 2 个条目中得到了 NaN，如何在不覆盖 NaN 的情况下获得以下结果？谢谢!

    Name    Score   English Science Math    Favourite_Subject   Final_Score
0   tom       31       50    30      20         English          81
1   nick      30       42    23      21         Math             51
2   juli      39       14    40      38         Science          79

Answer 1

我们可以使用lookup找到Favourite_Subject对应的分数，然后将它们与Current_Score相加计算Final_Score

i = df.columns.get_indexer(df['Favourite_Subject'])
df['Final_Score'] = df['Current_Score'] + df.values[df.index, i]

---

   Name  Current_Score  English  Science  Math Favourite_Subject Final_Score
0   tom             31       50       30    20           English          81
1  nick             30       42       23    21              Math          51
2  juli             39       14       40    38           Science          79