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https://github.com/yashksaini-coder/zomato-data-analysis
Zomato Data Analysis to explore insights and build predictive models with a dynamic & Interactive dashboard using Streamlit Web application. Also deploying and scaling with Cyclops-UI
https://github.com/yashksaini-coder/zomato-data-analysis
data-analysis docker kubernets streamlit streamlit-webapp
Last synced: 1 day ago
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Zomato Data Analysis to explore insights and build predictive models with a dynamic & Interactive dashboard using Streamlit Web application. Also deploying and scaling with Cyclops-UI
- Host: GitHub
- URL: https://github.com/yashksaini-coder/zomato-data-analysis
- Owner: yashksaini-coder
- License: mit
- Created: 2024-07-16T08:34:26.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-08-16T07:59:55.000Z (6 months ago)
- Last Synced: 2024-08-16T09:03:47.025Z (6 months ago)
- Topics: data-analysis, docker, kubernets, streamlit, streamlit-webapp
- Language: Jupyter Notebook
- Homepage:
- Size: 4.12 MB
- Stars: 8
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
[](https://github.com/yashksaini-coder/Zomato-Data-Analysis/actions/workflows/docker-publish.yml)
## 🚀 Project Overview
In this project, we delve into the fascinating world of restaurant data, exploring various aspects such as customer behavior, sales patterns, and operational efficiencies. Our goal is to extract actionable insights that can drive strategic decisions and foster growth in the competitive restaurant industry.
📄 Task List can be found [here](DS-Internship-Task.pdf). Click the link to access the detailed task list for the Data Science Internship.
## 🔑 Key Features:
- 📊 **Data Analysis:** In-depth exploration of restaurant data to uncover trends, patterns, and anomalies.
- 📈 **Predictive Modeling:** Development of robust models to forecast future trends and assist in decision-making.
- 🖥️ **Interactive Dashboard:** A dynamic and interactive dashboard built with Streamlit, providing real-time insights and visualizations.
## 🛠️ Getting Started
To get started with this project, follow the steps below:
1. **Clone the Repository:**
```bash
git clone https://github.com/yashksaini-coder/Zomato-Data-Analysis
```
2. **Navigate to the Project Directory:**
```bash
cd Zomato-Data-Analysis
```
3. **Install the Required Packages:**
```bash
pip install -r requirements.txt
```
4. **Run the Streamlit App:**
```bash
streamlit run app.py
```
5. **Explore the Dashboard:**
Open the Streamlit app in your browser and start exploring the interactive dashboard.
## 📁 Project Structure
The project is structured as follows:
```bash
Zomato-Data-Analysis
├─ .streamlit/
│ └─ config.toml
├─ .vscode/
│ ├─ launch.json
│ └─ tasks.json
├─ data/
│ └─ data.csv
├─ .dockerignore
├─ .gitignore
├─ app.py
├─ docker-compose.debug.yml
├─ docker-compose.yml
├─ Dockerfile
├─ DS-Internship-Task.pdf
├─ Level-1.ipynb
├─ Level-2.ipynb
├─ Level-3.ipynb
├─ LICENSE
├─ README.md
└─ requirements.txt
```
- **data:** Contains the dataset used for analysis.
- **app.py:** Streamlit app for the interactive dashboard.
- **requirements.txt:** Required packages for the project.
### 🌟 Getting Started
To contribute to our project, follow these steps:
1. **Fork the Repository:** Click on the [Fork](https://github.com/yashksaini-coder/Zomato-Data-Analysis/fork) button at the top right corner of the repository page. This will create a copy of the repository in your GitHub account.
2. **Clone the Repository:** Open your terminal and navigate to the directory where you want to clone the repository. Use the following command to clone the repository to your local machine:
```bash
git clone https://github.com/your-username/Zomato-Data-Analysis
```
3. **Create a New Branch:** Before making any changes, create a new branch to work on. Use the following command to create a new branch:
```bash
git checkout -b your-branch-name
```
4. **Make Changes:** Make the necessary changes to the project files using your preferred text editor or IDE.
5. **Commit Changes:** Once you have made your changes, it's time to commit them. Use the following command to commit your changes:
```bash
git add .
git commit -m "Your commit message"
```
6. **Push Changes:** Push your changes to your forked repository using the following command:
```bash
git push origin your-branch-name
```
7. **Create a Pull Request:** Go to the original repository on GitHub and click on the "New Pull Request" button. Fill in the necessary details and submit your pull request.
### 🔄 Keeping Your Fork Up to Date
To keep your forked repository up to date with the original repository, follow these steps:
1. **Add the Upstream Remote:** In your terminal, navigate to your local repository and use the following command to add the upstream remote:
```bash
git remote add upstream https://github.com/yashksaini-coder/Zomato-Data-Analysis.git
```
2. **Fetch the Latest Changes:** Use the following command to fetch the latest changes from the upstream repository:
```bash
git fetch upstream
```
3. **Merge the Changes:** Once you have fetched the latest changes, use the following command to merge them into your local branch:
```bash
git merge upstream/main
```
4. **Push the Changes:** Finally, push the merged changes to your forked repository using the following command:
```bash
git push origin your-branch-name
```
## 📜 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
Happy Coding! 🎉