(Python Example for Beginners)
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).
Test Data:
ord_no purch_amt ord_date customer_id salesman_id 0 70001 150.50 2012-10-05 3005 5002 1 70009 270.65 2012-09-10 3001 5005 2 70002 65.26 2012-10-05 3002 5001 3 70004 110.50 2012-08-17 3009 5003 4 70007 948.50 2012-09-10 3005 5002 5 70005 2400.60 2012-07-27 3007 5001 6 70008 5760.00 2012-09-10 3002 5001 7 70010 1983.43 2012-10-10 3004 5006 8 70003 2480.40 2012-10-10 3009 5003 9 70012 250.45 2012-06-27 3008 5002 10 70011 75.29 2012-08-17 3003 5007 11 70013 3045.60 2012-04-25 3002 5001
Sample Solution:
Python Code :
Sample Output:
Original Orders DataFrame: ord_no purch_amt ord_date customer_id salesman_id 0 70001 150.50 2012-10-05 3005 5002 1 70009 270.65 2012-09-10 3001 5005 2 70002 65.26 2012-10-05 3002 5001 3 70004 110.50 2012-08-17 3009 5003 4 70007 948.50 2012-09-10 3005 5002 5 70005 2400.60 2012-07-27 3007 5001 6 70008 5760.00 2012-09-10 3002 5001 7 70010 1983.43 2012-10-10 3004 5006 8 70003 2480.40 2012-10-10 3009 5003 9 70012 250.45 2012-06-27 3008 5002 10 70011 75.29 2012-08-17 3003 5007 11 70013 3045.60 2012-04-25 3002 5001 Mean, min, and max values of purchase amount (purch_amt) group by customer id (customer_id). purch_amt mean min max customer_id 3001 270.650000 270.65 270.65 3002 2956.953333 65.26 5760.00 3003 75.290000 75.29 75.29 3004 1983.430000 1983.43 1983.43 3005 549.500000 150.50 948.50 3007 2400.600000 2400.60 2400.60 3008 250.450000 250.45 250.45 3009 1295.450000 110.50 2480.40
Learn By Coding Examples
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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