Please note, this is a STATIC archive of website www.w3resource.com from 19 Jul 2022, cach3.com does not collect or store any user information, there is no "phishing" involved.
w3resource

Pandas: GroupBy with condition of two labels and ranges

Pandas Grouping and Aggregating: Split-Apply-Combine Exercise-29 with Solution

Write a Pandas program to split a given dataset using group by on specified column into two labels and ranges.

Split the group on 'salesman_id',
Ranges:
1) (5001...5006)
2) (5007..5012)

Test Data:

    salesman_id  sale_jan
0          5001    150.50
1          5002    270.65
2          5003     65.26
3          5004    110.50
4          5005    948.50
5          5006   2400.60
6          5007   1760.00
7          5008   2983.43
8          5009    480.40
9          5010   1250.45
10         5011     75.29
11         5012   1045.60

Sample Solution:

Python Code :

import pandas as pd
import numpy as np
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
df = pd.DataFrame({
'salesman_id': [5001,5002,5003,5004,5005,5006,5007,5008,5009,5010,5011,5012],
'sale_jan':[150.5, 270.65, 65.26, 110.5, 948.5, 2400.6, 1760, 2983.43, 480.4,  1250.45, 75.29,1045.6]})
print("Original Orders DataFrame:")
print(df)
result = df.groupby(pd.cut(df['salesman_id'], 
                  bins=[0,5006,np.inf],  
                  labels=['S1', 'S2']))['sale_jan'].sum().reset_index()
print("\nGroupBy with condition of  two labels and ranges:")
print(result)

Sample Output:

Original Orders DataFrame:
    salesman_id  sale_jan
0          5001    150.50
1          5002    270.65
2          5003     65.26
3          5004    110.50
4          5005    948.50
5          5006   2400.60
6          5007   1760.00
7          5008   2983.43
8          5009    480.40
9          5010   1250.45
10         5011     75.29
11         5012   1045.60

GroupBy with condition of  two labels and ranges:
  salesman_id  sale_jan
0          S1   3946.01
1          S2   7595.17

Python Code Editor:


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

Previous: Write a Pandas program to split a given dataset, group by one column and remove those groups if all the values of a specific columns are not available.
Next: Write a Pandas program to split the following dataset using group by on first column and aggregate over multiple lists on second column.

What is the difficulty level of this exercise?

Test your Programming skills with w3resource's quiz.



Python: Tips of the Day

Find current directory and file's directory:

To get the full path to the directory a Python file is contained in, write this in that file:

import os 
dir_path = os.path.dirname(os.path.realpath(__file__))

(Note that the incantation above won't work if you've already used os.chdir() to change your current working directory, since the value of the __file__ constant is relative to the current working directory and is not changed by an os.chdir() call.)

To get the current working directory use

import os
cwd = os.getcwd()

Documentation references for the modules, constants and functions used above:

  • The os and os.path modules.
  • The __file__ constant
  • os.path.realpath(path) (returns "the canonical path of the specified filename, eliminating any symbolic links encountered in the path")
  • os.path.dirname(path) (returns "the directory name of pathname path")
  • os.getcwd() (returns "a string representing the current working directory")
  • os.chdir(path) ("change the current working directory to path")

Ref: https://bit.ly/3fy0R6m