https://github.com/whatyuupratama/belajar_analisis_data_dengan_python
Capstone Class : Belajar Analisis Data dengan Python CodingCamp 2025
https://github.com/whatyuupratama/belajar_analisis_data_dengan_python
dicoding-submission ipython-notebook pandas python3 streamlit-dashboard
Last synced: 9 months ago
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Capstone Class : Belajar Analisis Data dengan Python CodingCamp 2025
- Host: GitHub
- URL: https://github.com/whatyuupratama/belajar_analisis_data_dengan_python
- Owner: whatyuupratama
- Created: 2025-03-08T12:43:45.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-17T16:18:19.000Z (about 1 year ago)
- Last Synced: 2025-06-17T17:30:47.234Z (about 1 year ago)
- Topics: dicoding-submission, ipython-notebook, pandas, python3, streamlit-dashboard
- Language: Jupyter Notebook
- Homepage: https://whatyuupratama-belajar-analisis-data--dashboardstreamlit-f4qxhz.streamlit.app/
- Size: 972 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 🚲 Analisis Sewa Sepeda dari Dataset Bike Sharing 📊
Heyy welcome to the **Analisis Sewa Sepeda dari Dataset Bike Sharing** project! 🚀
---
## 🚀 Getting Started
Follow these steps to set up and run the project locally:
### 1. Clone the Repository
```bash
git clone https://github.com/whatyuupratama/Belajar_Analisis_Data_dengan_Python.git
```
### 2. Navigate to the Project Directory
```bash
cd Belajar Analisis Data dengan Python
```
### 3. Install Dependencies
Make sure you have Python installed, then run:
```bash
pip install -r requirements.txt
```
### 4. Set Up Environment (Optional)
If you're using a virtual environment (recommended), create and activate it:
- **Linux/MacOS:**
```bash
python3 -m venv venv
source venv/bin/activate
```
- **Windows:**
```bash
python -m venv venv
.\venv\Scripts\activate
```
### 5. Run the Project
To run the dashboard using Streamlit:
```bash
streamlit run dashboard/streamlit.py
```
---
## 📦 Features
- 📊 **Data Analysis**: Insight into rental trends based on time and seasons.
- 🌐 **Interactive Dashboard**: Visualize data with Streamlit.
- 🧹 **Data Extraction**: Automatically extracts data from a ZIP file.
---
## 🖍️ Project Structure
```
🗁 Belajar_Analisis_Data_dengan_Python
🗋 dashboard
🗊 streamlit.py # Streamlit interactive dashboard
🗊 Bike-sharing-dataset.zip # Data file in ZIP format
🗋 data
🗊 day.csv # Daily data
🗊 hour.csv # Hourly data
🗍 Proyek_Analisis_Data.ipynb # Jupyter notebook for analysis
🗍 requirements.txt # Python dependencies
```
---
## 👩💻 Technologies Used
- **Frontend**: Streamlit (for interactive dashboard)
- **Backend**: Python
- **Data**: CSV files, ZIP extraction
- **Tools**: Pandas, Matplotlib, Streamlit
## 📚 Learn More
Check out these resources for additional information:
- [Streamlit Documentation](https://docs.streamlit.io/)
- [Pandas Documentation](https://pandas.pydata.org/pandas-docs/stable/)
- [Python Documentation](https://docs.python.org/3/)
---
## 🤝 Contributing
Contributions are welcome! To contribute:
1. Fork the repository.
2. Create a feature branch (`git checkout -b feature-name`).
3. Commit your changes (`git commit -m "Add feature"`).
4. Push to the branch (`git push origin feature-name`).
5. Create a pull request.
---
## 📧 Contact
Feel free to reach out for support or collaboration:
- **Email**: wahyupratamaa.id@gmail.com
- **GitHub**: [Your GitHub Profile](https://github.com/whatyuupratama)
---
## 🚀 Quick Start Commands
Here’s a summary of the commands you’ll use frequently:
1. Install dependencies:
```bash
pip install -r requirements.txt
```
2. Run the Streamlit app:
```bash
streamlit run dashboard/streamlit.py
```
3. Run the Jupyter Notebook:
```bash
jupyter notebook Proyek_Analisis_Data.ipynb
```