Metadata-Version: 2.1
Name: mycustomersegmentation
Version: 0.1.0
Summary: A python package for customer segmentation
Home-page: https://github.com/Margarita220103/mycustomersegmentation
Author: Margarita Harutyunyan
Author-email: maga220103@gmail.com
License: MIT license
Description: # Customer Segmentation Package
        
        This package provides functions for customer data analysis and segmentation.
        
        ## Description and Features
        
        The Customer Segmentation Package is designed to help analyze and segment customer data. It includes the following features:
        
        - Loading customer data from a CSV file
        - Finding missing values in the data
        - Performing exploratory data analysis
        - Plotting histograms and pair plots
        - Converting string columns to datetime objects
        - Performing K-means clustering on customer data
        - Performing customer segmentation using K-means clustering
        - Plotting scatter plots for each cluster based on two columns of data
        
        ## Installation
        
        You can install the Customer Segmentation Package using pip:
        
        ```bash
        pip install mycustomersegmentation
        ```
        
        ## Usage Examples
        
        Here are some examples of how you can use the Customer Segmentation Package for customer segmentation:
        
        ```python
        import pandas as pd
        from mycustomersegmentation import *
        
        # Load customer data
        data = load_data("customer_data.csv")
        
        # Find missing values
        missing_values = find_missing_values(data)
        print(missing_values)
        
        # Perform exploratory data analysis
        perform_eda(data)
        
        # Plot histograms
        columns = ["age", "income"]
        plot_histograms(data, columns)
        
        # Generate pairplot
        plot_pairplot(data)
        
        # Convert string column to datetime
        data = convert_to_datetime(data, "date")
        
        # Perform customer segmentation
        num_clusters = 4
        segmentation = customer_segmentation(data, num_clusters)
        print(segmentation)
        
        # Plot scatter plots for each cluster
        column1 = "age"
        column2 = "income"
        plot_cluster_scatter(data, column1, column2, num_clusters)
        ```
        ## How it Can Be Used in Customer Segmentation
        
        Customer segmentation is a common technique used in marketing and business analytics to divide a customer base into groups based on similar characteristics. This package provides a set of functions that can be used to analyze customer data, identify patterns, and perform clustering algorithms to segment customers into distinct groups. By understanding the different customer segments, businesses can tailor their marketing strategies, product offerings, and customer experiences to better meet the needs and preferences of each segment.
        
        ## License
        This package is released under the MIT License. See [MIT](https://opensource.org/license/mit/).
        
        Credits
        -------
        
        This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
        
        .. _Cookiecutter: https://github.com/audreyr/cookiecutter
        .. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
        
Keywords: mycustomersegmentation
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
