Metadata-Version: 2.1
Name: markbassmodel
Version: 0.1.0
Summary: This is a package containing several bass model functions that are useful for solving or evaluating marketing related problems 
Home-page: https://github.com/anukzak22/markbassmodel
Author: Anahit Zakaryan
Author-email: anukzak@gmail.com
License: MIT license
Keywords: markbassmodel
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
License-File: LICENSE
License-File: AUTHORS.rst
Requires-Dist: numpy (>=1.10)
Requires-Dist: pandas
Requires-Dist: matplotlib.pyplot
Requires-Dist: math
Requires-Dist: scipy.optimize


# markbassmodel

The **markbassmodel** package is a Python package that provides functions for fitting and predicting using the Bass diffusion model.

To forecast how quickly new items will be adopted in a market, the Bass model is a well-liked method in marketing analytics. The Bass model package can be used to aid with a number of issues relating to the marketing and adoption of new products, such as:

- Forecasting product sales
- Estimating the market potential with diffusion
- Comparing the performance of different products

## Functions



'diffusion(sales)'
This function calculates the cumulative diffusion curve for a given set of data's slaes column.

'adoption_rate(t, p, q, m, N)'
This function calculates the adoption rate for a given set of parameters and time.

'bass_f(t, p, q)'
This function calculates the Bass diffusion curve for a given set of parameters and time.

'bass_F(t, p, q)'
This function calculates the cumulative Bass diffusion curve for a given set of parameters and time.

'predict_bass_model(params, m)'
This function predicts the diffusion of a new product using the parameters p and q and the total market potential m.

'plot_bass(p, q, title)'
This function plots the Bass diffusion curve for a given set of parameters.

## Installation

To install the bassmodel package, you can use pip:

```
pip install markbassmodel
```
## Usage

To use the markbassmodel package, first import it:
```
import markbassmodel
```

calculate the parameters 

```
diffusion(sales)
```

plot the Bass diffusion curve:
```
bassmodel.plot_bass(params['p'], params['q'], 'Bass diffusion curve')
```


Sample data to check the package 

[ https://drive.google.com/drive/folders/1rtiKrg9xa2TMH8cTqN2l-eHWqQG1ZH6c?usp=sharing ]

the data contain smartphones sales over some period 
git
