Pandas Example – Write a Pandas program to join the two dataframes with matching records from both sides where available

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(Python Example for Beginners)

 

Write a Pandas program to join the two dataframes with matching records from both sides where available.

 

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(student_data2)

merged_data = pd.merge(student_data1, student_data2, on='student_id', how='outer')
print("Merged data (outer join):")
print(merged_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
Merged data (outer join):
  student_id            name_x  marks_x            name_y  marks_y
0         S1  Danniella Fenton    200.0               NaN      NaN
1         S2      Ryder Storey    210.0               NaN      NaN
2         S3      Bryce Jensen    190.0               NaN      NaN
3         S4         Ed Bernal    222.0  Scarlette Fisher    201.0
4         S5       Kwame Morin    199.0  Carla Williamson    200.0
5         S6               NaN      NaN       Dante Morse    198.0
6         S7               NaN      NaN    Kaiser William    219.0
7         S8               NaN      NaN   Madeeha Preston    201.0

 

Pandas Example – Write a Pandas program to join the two dataframes with matching records from both sides where available

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Two Machine Learning Fields

There are two sides to machine learning:

  • Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
  • Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
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