Pandas Example – Write a Pandas program to split a given dataframe into groups and list all the keys from the GroupBy object

Hits: 7

(Python Example for Beginners)

 

Write a Pandas program to split a given dataframe into groups and list all the keys from the GroupBy object.

Test Data:

   school_code class            name date_Of_Birth   age  height  weight 
S1        s001     V  Alberto Franco     15/05/2002   12     173      35   
S2        s002     V    Gino Mcneill     17/05/2002   12     192      32   
S3        s003    VI     Ryan Parkes     16/02/1999   13     186      33   
S4        s001    VI    Eesha Hinton     25/09/1998   13     167      30   
S5        s002     V    Gino Mcneill     11/05/2002   14     151      31   
S6        s004    VI    David Parkes     15/09/1997   12     159      32 

 

Sample Solution:

Python Code :


import pandas as pd

pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)

df = 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(df)

print("nSplit the data on school_code:");
gp = df.groupby('school_code')

print("nList of all the keys:")
print(gp.groups.keys())

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 data on school_code:

List of all the keys:
dict_keys(['s001', 's002', 's003', 's004'])

 

Pandas Example – Write a Pandas program to split a given dataframe into groups and list all the keys from the GroupBy object

Sign up to get end-to-end “Learn By Coding” example.


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.
Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.