Iterating thru Pandas DataFrame, multiple columns-CodePudding

parsed_df

  student_name, course_id,  weight,
0   A   1   10
1   B   1   10
2   C   1   10
3   A   1   40
4   B   1   40
5   C   1   40
6   A   1   50
7   B   1   50
8   C   1   50
9   A   2   40
10  C   2   40
11  A   2   60
12  C   2   60
13  A   3   90
14  B   3   90
15  C   3   90
16  A   3   10
17  B   3   10
18  C   3   10

What's the best way to iterate thru for each student and course_id to summarize the weight of each course for each student? The return value of the weights should each add up to 100, if not it should return an error.

For example: calculated_df = parsed_df.groupby(['student_name','course_id'])['weight'].sum()

CodePudding user response：

import pandas as pd

df = pd.DataFrame({
    'student_name': ['A', 'B',  'C', 'A', 'B', 'C', 'A', 'B', 'C', 'A', 'C', 'A', 'C', 'A', 'B', 'C', 'A', 'B', 'C'],
    'course_id': [1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3],
    'weight': [10, 10, 10, 40, 40, 40, 50, 50, 50, 40, 40, 60, 60, 90, 90, 90, 10, 10, 9]
})

df = df.groupby(by=['student_name', 'course_id']).agg({'weight': 'sum'})
df.reset_index(inplace=True)

print(df)
#  student_name  course_id  weight
#0            A          1     100
#1            A          2     100
#2            A          3     100
#3            B          1     100
#4            B          3     100
#5            C          1     100
#6            C          2     100
#7            C          3      99 -> Intentionally adjusted to raise Exception

#To check if there is weight, which is not 100
for i, row in df.iterrows():
    if row['weight'] != 100:
        raise Exception(f"Student {row['student_name']}\'s Course ID {row['course_id']}: {row['weight']}")

Exception: Student C's Course ID 3: 99

CodePudding user response：

Just compare the sum to 100?

>>> df.groupby(['student_name', 'course_id'])['weight'].sum().eq(100).reset_index()

  student_name  course_id  weight
0            A          1    True
1            A          2    True
2            A          3    True
3            B          1    True
4            B          3    True
5            C          1    True
6            C          2    True
7            C          3    True