Python Assign values to new dataframe like a schedule based on multiple conditions from another dataframe

Question

I started with this dataframe that had 4 columns: Name, Hours, Start Date and End Date:

Name	Hours	Start Date	End Date	Total Days
Ashley	6	1	2	2
Bob	8	1	2	2
John	5	3	5	3
Chris	5	4	4	1

Where 1-5 in the Start Date and End Date columns correspond to Monday-Friday.
I need to output a new dataframe/table that looks like this:

Name	Monday	Tuesday	Wednesday	Thursday	Friday
Ashley	6	6
Bob	8	8
John			5	5	5
Chris				5

I figured I’d make a dictionary to map 1 thru 5 to M thru F.
I then calculated the 4th column, "Total Days", thinking maybe I could first map the respective hours to the Starting Date and then use the total days values to have it iterate that many columns after, but I’m totally lost.

Answer 1

Let's try:

import calendar
df['days'] = df.apply(lambda x: np.arange(x['Start Date'], x['End Date']+1), axis=1)
dfe = df.explode('days')
df_out = dfe.pivot_table('Hours', 'Name', 'days', aggfunc='sum', fill_value=0)\
            .rename(columns=dict(enumerate(calendar.day_name, 1)))
print(df_out)

Output:

days    Monday  Tuesday  Wednesday  Thursday  Friday
Name                                                
Ashley       6        6          0         0       0
Bob          8        8          0         0       0
Chris        0        0          0         5       0
John         0        0          5         5       5