Pandas: Join two dataframes along columns

Pandas Joining and merging DataFrame: Exercise-2 with Solution

Write a Pandas program to join the two given dataframes along columns and assign all data.

Test Data:

student_data1:
  student_id              name  marks
0         S1  Danniella Fenton    200
1         S2      Ryder Storey    210
2         S3      Bryce Jensen    190
3         S4         Ed Bernal    222
4         S5       Kwame Morin    199

student_data2:
  student_id              name  marks
0         S4  Scarlette Fisher    201
1         S5  Carla Williamson    200
2         S6       Dante Morse    198
3         S7    Kaiser William    219
4         S8   Madeeha Preston    201

Sample Solution:

Python Code :

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]})

print("Original DataFrames:")
print(student_data1)
print("-------------------------------------")
print(student_data2)
print("\nJoin the said two dataframes along columns:")
result_data = pd.concat([student_data1, student_data2], axis = 1)
print(result_data)

Sample Output:

Original DataFrames:
  student_id              name  marks
0         S1  Danniella Fenton    200
1         S2      Ryder Storey    210
2         S3      Bryce Jensen    190
3         S4         Ed Bernal    222
4         S5       Kwame Morin    199
-------------------------------------
  student_id              name  marks
0         S4  Scarlette Fisher    201
1         S5  Carla Williamson    200
2         S6       Dante Morse    198
3         S7    Kaiser William    219
4         S8   Madeeha Preston    201

Join the said two dataframes along columns:
  student_id              name  marks student_id              name  marks
0         S1  Danniella Fenton    200         S4  Scarlette Fisher    201
1         S2      Ryder Storey    210         S5  Carla Williamson    200
2         S3      Bryce Jensen    190         S6       Dante Morse    198
3         S4         Ed Bernal    222         S7    Kaiser William    219
4         S5       Kwame Morin    199         S8   Madeeha Preston    201           

Python Code Editor:

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