(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 :
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
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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