w3resource

Pandas: Split a specified dataframe into groups by school code and get mean, min, and max value of age with customized column name for each school

Pandas Grouping and Aggregating: Split-Apply-Combine Exercise-22 with Solution

Write a Pandas program to split the following dataframe into groups by school code and get mean, min, and max value of age with customized column name for each school.

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('\nMean, min, and max value of age for each school with customized column names:')
grouped_single = student_data.groupby('school_code').agg(Age_Mean = ('age','mean'),Age_Max=('age',max),Age_Min=('age',min))
print(grouped_single)

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]

Mean, min, and max value of age for each school with customized column names:
             Age_Mean  Age_Max  Age_Min
school_code                            
s001             12.5       13       12
s002             13.0       14       12
s003             13.0       13       13
s004             12.0       12       12

Note: Run on Spyder Python 3.7.1

Python Code Editor:


Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous: Write a Pandas program to split the following dataframe into groups and calculate quarterly purchase amount.

Next: Write a Pandas program to split the following given datasets into groups on customer id and calculate the number of customers starting with 'C', the list of all products and the difference of maximum purchase amount and minimum purchase amount.

What is the difficulty level of this exercise?

Test your Python skills with w3resource's quiz



Python: Tips of the Day

Returns True if there are duplicate values in a flat list, False otherwise

Example:

def tips_duplicates(lst):
  return len(lst) != len(set(lst))

x = [2, 4, 6, 8, 4, 2]
y = [1, 3, 5, 7, 9]
print(tips_duplicates(x))
print(tips_duplicates(y))

Output:

True
False