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
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
Requires-Dist: pandas
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: scikit-learn

# 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


