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https://github.com/henrique-efonseca/salary-range-distribution-tool
A web application to help job applicants propose an optimal salary within a given range using a normal distribution approach. Built with Python, Flask, Numpy, Scipy and JavaScript.
https://github.com/henrique-efonseca/salary-range-distribution-tool
flask javascript numpy python scipy
Last synced: about 1 month ago
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A web application to help job applicants propose an optimal salary within a given range using a normal distribution approach. Built with Python, Flask, Numpy, Scipy and JavaScript.
- Host: GitHub
- URL: https://github.com/henrique-efonseca/salary-range-distribution-tool
- Owner: henrique-efonseca
- License: mit
- Created: 2024-07-08T17:25:54.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2024-07-08T19:44:39.000Z (4 months ago)
- Last Synced: 2024-10-02T06:02:46.212Z (about 2 months ago)
- Topics: flask, javascript, numpy, python, scipy
- Language: JavaScript
- Homepage:
- Size: 111 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Salary Range Distribution Tool
This tool helps job applicants determine an appropriate salary to propose when applying for a job or to understand their market value based on a normal distribution curve.
## Features
- Calculate salary distribution based on salary range.
- Generate a normal distribution curve.
- Provide percentile values to help understand the salary distribution.
## Screenshots
## How to Use
1. **Market Value Estimation**:
- Input the salary range based on market data for a specific role in a country to see the salary distribution around that range. This helps you understand your market value based on your perceived quality and experience.
2. **Specific Job Position**:
- Input the salary range for that position to see the distribution. If you know the salary range and the quality of employees in the same position at the company, you can use the distribution to find where you fit. For instance, if you think you are better than 30% of the current employees in the company for the same position, you could aim for the top 30% of the salary in that position.
## Installation
### Prerequisites
- Python 3.6+
- Virtualenv
### Steps
1. Clone the repository:
```bash
git clone https://github.com/henrique-efonseca/salary-range-distribution-tool.git
cd salary-range-distribution-tool
```
2. Create and activate a virtual environment:
```bash
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
```
3. Install the required dependencies:
```bash
pip install -r requirements.txt
```
4. Run the Flask application:
```bash
python run.py
```
5. Open your browser and navigate to `http://127.0.0.1:5000`.