Create nested dictionary from three separate lists with different length

Question

I need to create one nested dictionary to describe six (6) students scores for 3 exams:

dd = {
    'T': {'Exam 1': 100, 'Exam 2': 90, 'Exam 3': 80},
    'M': {'Exam 1': 88, 'Exam 2': 99, 'Exam 3': 111},
    'F': {'Exam 1': 45, 'Exam 2': 56, 'Exam 3': 67},
    'R': {'Exam 1': 59, 'Exam 2': 61, 'Exam 3': 67},
    'U': {'Exam 1': 73, 'Exam 2': 79, 'Exam 3': 83},
    'F': {'Exam 1': 89, 'Exam 2': 97, 'Exam 3': 101}
}

Original input and prep are:

import pandas as pd

grades = [
    ['Student', 'Exam 1', 'Exam 2', 'Exam 3'],
    ['T', '100', '90', '80'],
    ['M', '88', '99', '111'],
    ['F', '45', '56', '67'],
    ['R', '59', '61', '67'],
    ['U', '73', '79', '83'],
    ['F', '89', '97', '101']
]

headers = grades.pop(0)
df = pd.DataFrame(grades, columns=headers)

df[['Exam 1','Exam 2','Exam 3']] = df[['Exam 1','Exam 2','Exam 3']].astype(int)

I can create the lists for dictionary creation:

students = df['Student'].tolist()
assignments = list(df.columns.values)
assignments.remove('Student')

Problem:

internal dictionary: keys - assignment (3), values - scores (6) Outer dictionary: keys - students (6), values - assignments (3)

I do not know how to handle the scores list!! It is 6 per assignment but is it a list of lists (3 x 6)??

I would like to use the zip function:

keys = students
values = assignments

result = dict(zip(keys, values))

but I do not know how to iterate internal dictionary:

keys = assignments. (3 elements)
values = scores (has to be 3 by 6) #-  how to iterate it if it is possible at all?

result = dict(zip(keys, values))

Answer 1

You can use pandas to_dict function directly on your dataframe. However, your dataframe has duplicate students, so you won't be able to get your example dictionary exactly (must have unique keys).

Removing the duplicate "F" student for illustration...

import pandas as pd

grades = [

    ['Student', 'Exam 1', 'Exam 2', 'Exam 3'],
    ['T', '100', '90', '80'],
    ['M', '88', '99', '111'],
    ['F', '45', '56', '67'],
    ['R', '59', '61', '67'],
    ['U', '73', '79', '83']
]

headers = grades.pop(0)
df = pd.DataFrame(grades, columns=headers)

df[['Exam 1','Exam 2','Exam 3']] = df[['Exam 1','Exam 2','Exam 3']].astype(int)

df = df.set_index('Student')
dd = df.to_dict(orient='index')

print(dd)

{'T': {'Exam 1': 100, 'Exam 2': 90, 'Exam 3': 80}, 
'M': {'Exam 1': 88, 'Exam 2': 99, 'Exam 3': 111}, 
'F': {'Exam 1': 45, 'Exam 2': 56, 'Exam 3': 67}, 
'R': {'Exam 1': 59, 'Exam 2': 61, 'Exam 3': 67}, 
'U': {'Exam 1': 73, 'Exam 2': 79, 'Exam 3': 83}}

Answer 2

First, you have two students named "F" but dict keys have to be unique. You could then try the following:

grades = [
    ['Student', 'Exam 1', 'Exam 2', 'Exam 3'],
    ['T', '100', '90', '80'],
    ['M', '88', '99', '111'],
    ['F', '45', '56', '67'],
    ['R', '59', '61', '67'],
    ['U', '73', '79', '83'],
    ['F', '89', '97', '101']
]

dd = {}
for name, exam1, exam2, exam3 in grades[1:]:
    dd[name] = {'Exam 1': exam1, 'Exam 2': exam2, 'Exam 3': exam3}

or:

keys = [keys[0] for keys in grades[1:]]
values = [dict(zip(['Exam 1', 'Exam 2', 'Exam 3'], keys[1:])) for keys in grades[1:]]
dd = dict(zip(keys, values))