https://github.com/SimranShaikh20/Customer-Salary-Based-on-Experience
A Data Analysts Project for Salary Prediction Based On Experiences .
https://github.com/SimranShaikh20/Customer-Salary-Based-on-Experience
Last synced: 11 months ago
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A Data Analysts Project for Salary Prediction Based On Experiences .
- Host: GitHub
- URL: https://github.com/SimranShaikh20/Customer-Salary-Based-on-Experience
- Owner: SimranShaikh20
- Created: 2024-06-13T13:23:19.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-06-13T13:24:18.000Z (about 2 years ago)
- Last Synced: 2024-06-13T15:59:43.071Z (about 2 years ago)
- Language: Jupyter Notebook
- Size: 29.3 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 📊 Customer Salary Based on Experience
## 📌 Project Overview
This project focuses on analyzing and predicting salary expectations based on professional experience. Using data analysis, visualization, and predictive modeling techniques, it uncovers trends and patterns in salary expectations.
---
## 📜 Table of Contents
1. [📖 Introduction](#-introduction)
2. [✨ Features](#-features)
3. [🛠 Technologies Used](#-technologies-used)
4. [🚀 Setup Instructions](#-setup-instructions)
5. [📈 Data Analysis Steps](#-data-analysis-steps)
6. [🔍 Conclusion](#-conclusion)
7. [🙏 Acknowledgements](#-acknowledgements)
---
## 📖 Introduction
The goal of this project is to help individuals and organizations better understand the relationship between experience levels and salary expectations. By analyzing a dataset, the project provides insights and predictions using statistical and machine learning methods.
---
## ✨ Features
✅ **Data Analysis**: In-depth analysis of salary trends based on years of experience.
📊 **Visualizations**: Graphs and charts for easy interpretation of salary data.
🤖 **Predictive Modeling**: Machine learning models to predict expected salaries.
📜 **Interactive Notebook**: All steps are documented for reproducibility.
---
## 🛠 Technologies Used
- **🐍 Python 3.11.5**
- **Libraries**:
- 📊 Pandas (Data manipulation)
- 📉 Matplotlib/Seaborn (Data visualization)
- 🤖 Scikit-learn (Machine learning modeling)
- **📓 Jupyter Notebook** for interactive analysis.
---
## 🚀 Setup Instructions
Follow these steps to run the project locally:
1. Clone the repository:
```bash
git clone github.com/SimranShaikh20/Customer-Salary-Based-on-Experience
```
2. Navigate to the project directory:
```bash
cd salary-expectation-analysis
```
3. Install the dependencies:
```bash
pip install -r requirements.txt
```
4. Open the notebook:
```bash
jupyter notebook
```
---
## 📈 Data Analysis Steps
The notebook follows a structured workflow:
1. **📥 Data Collection**: Importing and cleaning the dataset.
2. **🔍 Exploratory Data Analysis (EDA)**:
- Identifying trends and patterns.
- Visualizing salary distributions.
3. **⚙ Feature Engineering**: Preparing the data for modeling.
4. **🤖 Modeling**:
- Implementing machine learning models to predict salary.
- Comparing model performance.
5. **📊 Insights**: Extracting conclusions and actionable insights.
---
## 🔍 Conclusion
This project provides a comprehensive understanding of how experience influences salary expectations. It combines analytical and predictive tools to deliver valuable insights for professionals and organizations.
---
## 🙏 Acknowledgements
Thank you for exploring this project! 😊 Feel free to contribute or share your feedback.
---
👩💻 **Author**: Simran
🛠 **Tools**: Jupyter Notebook, Python
---