import numpy as np
import pandas as pd
grades_module1 = {'Marvin Minsky': 5.7, 'John McCarthy': 6.2, 'Claude Shannon': 6.5, 'Alan Turing': 7.0}
grades_module2 = [('Marvin Minsky', 8.0), ('John McCarthy', 8.5), ('Claude Shannon', 8.0), ('Alan Turing', 9.0)]
grades_module3 = {('Marvin Minsky', 9.5), ('John McCarthy', 8.9), ('Claude Shannon', 8.7), ('Alan Turing', 9.1)}
grades_module4 = [3.3, 4.5, 6.7, 8.9]
import numpy as np
grades_module5 = np.array([3.5, 4.1, 2.1, 9.3])
grades_module6 = pd.Series([8.3, 6.5, 5.7, 5.9])
grades_module7 = pd.Series([3.3, 4.5, 6.7, 8.9], index=['Marvin Minsky', 'John McCarthy', 'Claude Shannon', 'Alan Turing'])
grades_module8 = pd.Series({'Marvin Minsky': 5.7, 'John McCarthy': 6.2, 'Claude Shannon': 6.5, 'Alan Turing': 7.0})
# grades_module6.index= ['Marvin Minsky', 'John McCarthy', 'Claude Shannon', 'Alan Turing']
df = pd.DataFrame({
'Module 1': grades_module1,
'Module 2': dict(grades_module2),
'Module 3': dict(grades_module3),
'Module 4': pd.Series(grades_module4, index=['Marvin Minsky', 'John McCarthy', 'Claude Shannon', 'Alan Turing']),
'Module 5': pd.Series(grades_module5, index=['Marvin Minsky', 'John McCarthy', 'Claude Shannon', 'Alan Turing']),
'Module 6': pd.Series(grades_module6.values, index=['Marvin Minsky', 'John McCarthy', 'Claude Shannon', 'Alan Turing']),
# 'Module 6': dict(zip(['Marvin Minsky', 'John McCarthy', 'Claude Shannon', 'Alan Turing'], grades_module6.values)),
'Module 7': grades_module7,
'Module 8': grades_module8
})
df
|
Module 1 |
Module 2 |
Module 3 |
Module 4 |
Module 5 |
Module 6 |
Module 7 |
Module 8 |
| Marvin Minsky |
5.7 |
8.0 |
9.5 |
3.3 |
3.5 |
8.3 |
3.3 |
5.7 |
| John McCarthy |
6.2 |
8.5 |
8.9 |
4.5 |
4.1 |
6.5 |
4.5 |
6.2 |
| Claude Shannon |
6.5 |
8.0 |
8.7 |
6.7 |
2.1 |
5.7 |
6.7 |
6.5 |
| Alan Turing |
7.0 |
9.0 |
9.1 |
8.9 |
9.3 |
5.9 |
8.9 |
7.0 |