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Pandas Example – Write a Pandas program to split a given dataset using group by on multiple columns and drop last n rows of from each group

By on Wednesday, April 14, 2021

(Python Example for Beginners)

 

Write a Pandas program to split a given dataset using group by on multiple columns and drop last n rows of from each group.

 

Test Data:

    ord_no  purch_amt    ord_date  customer_id  salesman_id
0    70001     150.50  2012-10-05         3002         5002
1    70009     270.65  2012-09-10         3001         5003
2    70002      65.26  2012-10-05         3001         5001
3    70004     110.50  2012-08-17         3003         5003
4    70007     948.50  2012-09-10         3002         5002
5    70005    2400.60  2012-07-27         3002         5001
6    70008    5760.00  2012-09-10         3001         5001
7    70010    1983.43  2012-10-10         3004         5003
8    70003    2480.40  2012-10-10         3003         5003
9    70012     250.45  2012-06-27         3002         5002
10   70011      75.29  2012-08-17         3003         5003
11   70013    3045.60  2012-04-25         3001         5001

 

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({
'ord_no':[70001,70009,70002,70004,70007,70005,70008,70010,70003,70012,70011,70013],
'purch_amt':[150.5,270.65,65.26,110.5,948.5,2400.6,5760,1983.43,2480.4,250.45, 75.29,3045.6],
'ord_date': ['2012-10-05','2012-09-10','2012-10-05','2012-08-17','2012-09-10','2012-07-27','2012-09-10','2012-10-10','2012-10-10','2012-06-27','2012-08-17','2012-04-25'],
'customer_id':[3002,3001,3001,3003,3002,3002,3001,3004,3003,3002,3003,3001],
'salesman_id':[5002,5003,5001,5003,5002,5001,5001,5003,5003,5002,5003,5001]})

print("Original Orders DataFrame:")
print(df)

print("nSplit the said data on 'salesman_id', 'customer_id' wise:")

result = df.groupby(['salesman_id', 'customer_id'])
for name,group in result:
    print("nGroup:")
    print(name)
    print(group)
n = 2

result1 = df.groupby(['salesman_id', 'customer_id']).tail(n).index, axis=0)

print("nDroping last two records:")    
result1 = df.drop(df.groupby(['salesman_id', 'customer_id']).tail(n).index, axis=0)
print(result1)

Sample Output:

Original Orders DataFrame:
    ord_no  purch_amt    ord_date  customer_id  salesman_id
0    70001     150.50  2012-10-05         3002         5002
1    70009     270.65  2012-09-10         3001         5003
2    70002      65.26  2012-10-05         3001         5001
3    70004     110.50  2012-08-17         3003         5003
4    70007     948.50  2012-09-10         3002         5002
5    70005    2400.60  2012-07-27         3002         5001
6    70008    5760.00  2012-09-10         3001         5001
7    70010    1983.43  2012-10-10         3004         5003
8    70003    2480.40  2012-10-10         3003         5003
9    70012     250.45  2012-06-27         3002         5002
10   70011      75.29  2012-08-17         3003         5003
11   70013    3045.60  2012-04-25         3001         5001

Split the said data on 'salesman_id', 'customer_id' wise:

Group:
(5001, 3001)
    ord_no  purch_amt    ord_date  customer_id  salesman_id
2    70002      65.26  2012-10-05         3001         5001
6    70008    5760.00  2012-09-10         3001         5001
11   70013    3045.60  2012-04-25         3001         5001

Group:
(5001, 3002)
   ord_no  purch_amt    ord_date  customer_id  salesman_id
5   70005     2400.6  2012-07-27         3002         5001

Group:
(5002, 3002)
   ord_no  purch_amt    ord_date  customer_id  salesman_id
0   70001     150.50  2012-10-05         3002         5002
4   70007     948.50  2012-09-10         3002         5002
9   70012     250.45  2012-06-27         3002         5002

Group:
(5003, 3001)
   ord_no  purch_amt    ord_date  customer_id  salesman_id
1   70009     270.65  2012-09-10         3001         5003

Group:
(5003, 3003)
    ord_no  purch_amt    ord_date  customer_id  salesman_id
3    70004     110.50  2012-08-17         3003         5003
8    70003    2480.40  2012-10-10         3003         5003
10   70011      75.29  2012-08-17         3003         5003

Group:
(5003, 3004)
   ord_no  purch_amt    ord_date  customer_id  salesman_id
7   70010    1983.43  2012-10-10         3004         5003

Droping last two records:
   ord_no  purch_amt    ord_date  customer_id  salesman_id
0   70001     150.50  2012-10-05         3002         5002
2   70002      65.26  2012-10-05         3001         5001
3   70004     110.50  2012-08-17         3003         5003

 

 

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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.
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