https://github.com/0xjonaseb11/vistor_mgt.2.0
A Vistor Management system built with Django | Datasets analysis | Feature Engineering
https://github.com/0xjonaseb11/vistor_mgt.2.0
datasets django fastapi feature-engineering python
Last synced: about 2 months ago
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A Vistor Management system built with Django | Datasets analysis | Feature Engineering
- Host: GitHub
- URL: https://github.com/0xjonaseb11/vistor_mgt.2.0
- Owner: 0xJonaseb11
- Created: 2024-11-29T09:26:57.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-12T08:25:36.000Z (over 1 year ago)
- Last Synced: 2025-01-20T14:58:33.091Z (over 1 year ago)
- Topics: datasets, django, fastapi, feature-engineering, python
- Language: Python
- Homepage:
- Size: 25.2 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# vistor_mgt.2.0
**(Visitor Management System v2.0)**
This project is a comprehensive Django-based application designed to demonstrate key data handling capabilities, including feature engineering, dataset management, and data preprocessing. The work aligns with quiz tasks such as:
1. Extracting large-scale data.
2. Dataset description.
3. Handling null values.
4. Data preprocessing.
5. Feature creation.
## Features
- **Return 500,000 Rows:** Efficiently manage large-scale datasets, enabling smooth retrieval of up to 500,000 rows.
- **Describe Dataset:** Provides detailed statistics and insights into the dataset, including types, distributions, and anomalies.
- **Handle Missing Values:** Locate and replace null values with suitable techniques (e.g., mean imputation, forward fill).
- **Data Preprocessing:** Perform essential preprocessing such as encoding categorical variables, normalization, and handling outliers.
- **Feature Engineering:** Create new features to enhance the model's performance or gain deeper insights into the dataset.
## Technology Stack
- **Backend:** Django 4.x
- **Database:** SQLite (or any preferred database)
- **Languages:** Python 3.x
- **Libraries:** Pandas, NumPy, and other relevant Python packages.
## Installation
1. Clone the repository:
```bash
git clone https://github.com/0xJonaseb11/vistor_mgt.2.0.git
```
2. Navigate to the project directory:
```bash
cd vistor_mgt.2.0
```
3. Create a virtual environment and activate it:
```bash
python3 -m venv env
source env/bin/activate # For Linux/MacOS
env\Scripts\activate # For Windows
```
4. Install dependencies:
```bash
pip install -r requirements.txt
```
5. Run the Django development server:
```bash
python manage.py runserver
```
6. Access the application at `http://127.0.0.1:8000/`.
## Usage
- **Returning Large Rows:**
Demonstrates efficient data handling for large-scale datasets with optimized queries and data processing.
- **Dataset Description:**
Use the built-in data analytics tools to explore and understand the dataset.
- **Handling Null Values:**
Flexible options to identify, replace, or drop null values based on user preferences.
- **Data Preprocessing:**
Provides pipelines for data cleaning, transformation, and preparation for analysis or machine learning models.
- **Feature Engineering:**
Implement advanced techniques to generate meaningful features and improve data quality.
## Contributions
Contributions are welcome! Please fork the repository and submit a pull request with your changes.
## License
This project is licensed under the MIT License. See the LICENSE file for details.
## Author
[0xJonaseb11](https://github.com/0xJonaseb11)