Pandas: Split the specified given dataframe into groups based on school code and call a specific group with the name of the group
6. Selecting a Specific Group
Write a Pandas program to split the following given dataframe into groups based on school code and call a specific group with the name of the group.
Test Data:
school class name date_Of_Birth age height weight address S1 s001 V Alberto Franco 15/05/2002 12 173 35 street1 S2 s002 V Gino Mcneill 17/05/2002 12 192 32 street2 S3 s003 VI Ryan Parkes 16/02/1999 13 186 33 street3 S4 s001 VI Eesha Hinton 25/09/1998 13 167 30 street1 S5 s002 V Gino Mcneill 11/05/2002 14 151 31 street2 S6 s004 VI David Parkes 15/09/1997 12 159 32 street4
Sample Solution:
Python Code :
import pandas as pd
pd.set_option('display.max_rows', None)
#pd.set_option('display.max_columns', None)
student_data = pd.DataFrame({
'school_code': ['s001','s002','s003','s001','s002','s004'],
'class': ['V', 'V', 'VI', 'VI', 'V', 'VI'],
'name': ['Alberto Franco','Gino Mcneill','Ryan Parkes', 'Eesha Hinton', 'Gino Mcneill', 'David Parkes'],
'date_Of_Birth ': ['15/05/2002','17/05/2002','16/02/1999','25/09/1998','11/05/2002','15/09/1997'],
'age': [12, 12, 13, 13, 14, 12],
'height': [173, 192, 186, 167, 151, 159],
'weight': [35, 32, 33, 30, 31, 32],
'address': ['street1', 'street2', 'street3', 'street1', 'street2', 'street4']},
index=['S1', 'S2', 'S3', 'S4', 'S5', 'S6'])
print("Original DataFrame:")
print(student_data)
print('\nSplit the said data on school_code wise:')
grouped = student_data.groupby(['school_code'])
print("Call school code 's001':")
print(grouped.get_group('s001'))
print("\nCall school code 's004':")
print(grouped.get_group('s004'))
Sample Output:
Original DataFrame: school_code class name ... height weight address S1 s001 V Alberto Franco ... 173 35 street1 S2 s002 V Gino Mcneill ... 192 32 street2 S3 s003 VI Ryan Parkes ... 186 33 street3 S4 s001 VI Eesha Hinton ... 167 30 street1 S5 s002 V Gino Mcneill ... 151 31 street2 S6 s004 VI David Parkes ... 159 32 street4 [6 rows x 8 columns] Split the said data on school_code wise: Call school code 's001': school_code class name ... height weight address S1 s001 V Alberto Franco ... 173 35 street1 S4 s001 VI Eesha Hinton ... 167 30 street1 [2 rows x 8 columns] Call school code 's004': school_code class name ... height weight address S6 s004 VI David Parkes ... 159 32 street4 [1 rows x 8 columns]
For more Practice: Solve these Related Problems:
- Write a Pandas program to group the dataframe by school code and then extract and display the group corresponding to a specific school code.
- Write a Pandas program to group the dataframe by school code and use the get_group() method to retrieve data for a given school.
- Write a Pandas program to group the dataframe by school code and then check the content of a specific group using its group key.
- Write a Pandas program to group the dataframe by school code and then verify the selected group's structure by printing its summary statistics.
Go to:
Previous: Write a Pandas program to split the following given dataframe into groups based on single column and multiple columns. Find the size of the grouped data.
Next: Write a Pandas program to split a dataset, group by one column and get mean, min, and max values by group. Using the following dataset find the mean, min, and max values of purchase amount (purch_amt) group by customer id (customer_id).
Python Code Editor:
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