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Categorizing Products based on the Sales Percentage in Pandas Dataframe

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by Abdul Rawoof A R dot icon Updated: Feb 21, 2023

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A pandas data type is categorical that corresponds to categorical variables in statistics, and its variables take on a limited, usually fixed, number of values. 


A hybrid data type is a category data type in pandas. It looks and behaves like a string in many instances but internally is represented by an array of integers in pandas. It allows the data to be stored in a custom order and to store the data or information efficiently. Product categorization is how a marketplace or ad platform groups our products into distinct, hierarchical categories, like the animal kingdom's classification. Channels have broad categories or taxonomies that branch into more specific panda groups. Proper categorization plays a significant role in product discoverability, how our product listings are displayed, and even how sales tax is calculated. Accurate product categorization improves advertising campaigns and operational procedures. 

  • Pandas: It is used to work with data sets and has functions for exploring, analyzing, manipulating data, and cleaning. 
  • NumPy: It is used to work with arrays and has functions for working in the domain of linear algebra and matrices. 


Here is an example of how to categorize products based on the sales percentage in Pandas DataFrame: 

Fig : Preview of the output that you will get on running this code from your IDE.

Code

In this solution we're using Pandas and NumPy libraries.

categorizing products based on the salePercentage in pandas Dataframe

PythondotLines of Code : 12dotLicense : Strong Copyleft (CC BY-SA 4.0)

Dependent Libraries : 
import pandas as pd
import numpy as np
in_data = np.random.random(10)
df = pd.DataFrame()
df['A'] = in_data
df['fraction'] = df['A'] / df['A'].sum()
df.sort_values(by='fraction', inplace=True)
df['csum'] = df.fraction.cumsum()
df_60 = df[df.csum <= 0.60]
df_30 = df[(df.csum > 0.60) & (df.csum <= 0.90)]
df_10 = df[df.csum > 0.90]

Instructions

Follow the steps carefully to get the output easily.

  1. Install pandas on your IDE(Any of your favorite IDE).
  2. Copy the snippet using the 'copy' and paste it in your IDE.
  3. Add required dependencies and import them in Python file.
  4. Run the file to generate the output.


I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.


I found this code snippet by searching for 'how to categorizing products based on the salepercentage in pandas' in kandi. You can try any such use case!

Environment Tested

I tested this solution in the following versions. Be mindful of changes when working with other versions.

  1. The solution is created in PyCharm 2021.3.
  2. The solution is tested on Python 3.9.7.
  3. Pandas version-v1.5.2.
  4. NumPy version-v1.24.0.


Using this solution, we are able to categorizing product based on the sale percentage in pandas data frame with simple steps. This process also facilities an easy way to use, hassle-free method to create a hands-on working version of code which would help us to categorizing product based on the sale percentage in pandas data frame.

Dependent Libraries

pandasby pandas-dev

Python doticonstar image 38689 doticonVersion:v2.0.2doticon
License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

Support
    Quality
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        License
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            pandasby pandas-dev

            Python doticon star image 38689 doticonVersion:v2.0.2doticon License: Permissive (BSD-3-Clause)

            Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
            Support
              Quality
                Security
                  License
                    Reuse

                      numpyby numpy

                      Python doticonstar image 23755 doticonVersion:v1.25.0rc1doticon
                      License: Permissive (BSD-3-Clause)

                      The fundamental package for scientific computing with Python.

                      Support
                        Quality
                          Security
                            License
                              Reuse

                                numpyby numpy

                                Python doticon star image 23755 doticonVersion:v1.25.0rc1doticon License: Permissive (BSD-3-Clause)

                                The fundamental package for scientific computing with Python.
                                Support
                                  Quality
                                    Security
                                      License
                                        Reuse

                                          You can also search for any dependent libraries on kandi like 'pandas' and 'numpy'.

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