(Python Example for Beginners)
Write a Pandas program to split the following dataframe into groups based on school code. Also check the type of GroupBy object.
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 :
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: Group: 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] Group: s002 school_code class name ... height weight address S2 s002 V Gino Mcneill ... 192 32 street2 S5 s002 V Gino Mcneill ... 151 31 street2 [2 rows x 8 columns] Group: s003 school_code class name ... height weight address S3 s003 VI Ryan Parkes ... 186 33 street3 [1 rows x 8 columns] Group: s004 school_code class name ... height weight address S6 s004 VI David Parkes ... 159 32 street4 [1 rows x 8 columns] Type of the object: <class 'pandas.core.groupby.groupby.DataFrameGroupBy'>
Pandas Example – Write a Pandas program to split the following dataframe into groups based on school code
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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