如何使用其他数据框列的值转换数据框的列值

Question

如何在orig_diff中添加列“ main_category”，该列将指示子类别属于哪个主要类别。 例如，值“电影”的orig_df必须将“ main_category”作为“娱乐”，将“ Maths”作为“教育”。

import pandas as pd
import numpy as np

orig_df = pd.DataFrame({"sub_cat" : ["Movie", "Science", "Maths", "Music", "Songs", "Dance", "English", "Maths", "Songs"], "Student": ["Stud1", "Stud2", "Stud3", "Stud4", "Stud5", "Stud6", "Stud7", "Sud8", "Stud9"]})
sub_df = pd.DataFrame({"Education": [0,1,1,0,0,0,1], "Entertainment": [1,0,0,1,1,1,0]}, index=["Movie", "Science", "Maths", "Music", "Songs", "Dance", "English"])
print(orig_df)
print(sub_df)

Answer 1

一种方法是通过迭代行从sub_df创建字典。

然后使用字典作为orig_df['sub_cat']上的地图：

d = {idx: next(k for k in sub_df if row[k]==1)
     for idx, row in sub_df.iterrows()}

orig_df['main_category'] = orig_df['sub_cat'].map(d)

print(orig_df)

  Student  sub_cat  main_category
0   Stud1    Movie  Entertainment
1   Stud2  Science      Education
2   Stud3    Maths      Education
3   Stud4    Music  Entertainment
4   Stud5    Songs  Entertainment
5   Stud6    Dance  Entertainment
6   Stud7  English      Education
7    Sud8    Maths      Education
8   Stud9    Songs  Entertainment

请注意，这假定每个sub_cat仅映射到“教育”或“娱乐”之一。