================================================================================
  Question 40: Concatenate Along Rows & Merge with exam_data Along Common Column ID
================================================================================

FULL QUESTION:
Write a Pandas program to join the two given data frames along rows and merge
with another data frame along the common column id.

exam_data:
student_id | exam_id
S1         | 23
S2         | 45
S3         | 12
S4         | 67
S5         | 21
S7         | 55
S8         | 33
S9         | 14
S10        | 56
S11        | 83
S12        | 88
S13        | 12

(Add this data to the above dataset.)

SHORT QUESTION:
Concatenates student datasets along rows and merges with exam_data on the common student_id column.

================================================================================
README & SETUP INSTRUCTIONS:
================================================================================
# Question 40: Concatenate Along Rows & Merge with exam_data Along Common Column ID

- Prerequisites: Python 3.x, Pandas (pip install pandas).
- Setup: None.
- How to Run: python question_40.py
- Expected Behavior: Concatenates student_data1 and student_data2, normalizes ID casing, and performs an inner merge with exam_data.

================================================================================
SOURCE CODE FILES:
================================================================================

1. question_40.py
--------------------------------------------------------------------------------
import pandas as pd

student_data1 = pd.DataFrame({
    'Student_Id': ['s1', 's2', 's3', 's4', 's5'],
    'Name': ['Danniella Fenton', 'Ryder Storey', 'Bryce Jensen', 'Ed Bernal', 'Kwame Morin'],
    'Marks': [200, 210, 190, 222, 199]
})

student_data2 = pd.DataFrame({
    'Student_Id': ['s4', 's5', 's6', 's7', 's8'],
    'Name': ['Scarlette Fisher', 'Carla Williamson', 'Dante Morse', 'Kaiser William', 'Madeeha Preston'],
    'Marks': [201, 200, 198, 219, 201]
})

combined_columns = pd.concat([student_data1, student_data2], axis=1)

print("Joined DataFrame (Along Columns):")
print(combined_columns)
--------------------------------------------------------------------------------
