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Pandas Example – Write a Pandas program to join the two given dataframes along rows and merge with another dataframe along the common column id

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(Python Example for Beginners)

 

Write a Pandas program to join the two given dataframes along rows and merge with another dataframe along the common column id.

 

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

exam_data:
   student_id  exam_id
0          S1       23
1          S2       45
2          S3       12
3          S4       67
4          S5       21
5          S7       55
6          S8       33
7          S9       14
8         S10       56
9         S11       83
10        S12       88
11        S13       12

 

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]})

exam_data = pd.DataFrame({
        'student_id': ['S1', 'S2', 'S3', 'S4', 'S5', 'S7', 'S8', 'S9', 'S10', 'S11', 'S12', 'S13'],
        'exam_id': [23, 45, 12, 67, 21, 55, 33, 14, 56, 83, 88, 12]})

print("Original DataFrames:")
print(student_data1)
print(student_data2)
print(exam_data)

print("nJoin first two said dataframes along rows:")
result_data = pd.concat([student_data1, student_data2])
print(result_data)

print("nNow join the said result_data and df_exam_data along student_id:")
final_merged_data = pd.merge(result_data, exam_data, on='student_id')
print(final_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
   student_id  exam_id
0          S1       23
1          S2       45
2          S3       12
3          S4       67
4          S5       21
5          S7       55
6          S8       33
7          S9       14
8         S10       56
9         S11       83
10        S12       88
11        S13       12

Join first two said dataframes along rows:
  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
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

Now join the said result_data and df_exam_data along student_id:
  student_id              name  marks  exam_id
0         S1  Danniella Fenton    200       23
1         S2      Ryder Storey    210       45
2         S3      Bryce Jensen    190       12
3         S4         Ed Bernal    222       67
4         S4  Scarlette Fisher    201       67
5         S5       Kwame Morin    199       21
6         S5  Carla Williamson    200       21
7         S7    Kaiser William    219       55
8         S8   Madeeha Preston    201       33

 

Pandas Example – Write a Pandas program to join the two given dataframes along rows and merge with another dataframe along the common column id

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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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