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https://github.com/andr3w03/bike-sharing-dashboard
Bike Sharing Data Analysis Streamlit Dashboard
https://github.com/andr3w03/bike-sharing-dashboard
dashboard data-analysis data-visualization python streamlit
Last synced: about 18 hours ago
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Bike Sharing Data Analysis Streamlit Dashboard
- Host: GitHub
- URL: https://github.com/andr3w03/bike-sharing-dashboard
- Owner: aNdr3W03
- Created: 2023-06-25T12:18:17.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-06-25T14:55:27.000Z (over 1 year ago)
- Last Synced: 2024-12-02T03:33:06.239Z (about 2 months ago)
- Topics: dashboard, data-analysis, data-visualization, python, streamlit
- Language: Jupyter Notebook
- Homepage: https://bike-sharing.streamlit.app
- Size: 6.75 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Bike Sharing Dashboard
Streamlit Cloud: Bike Sharing Dashboard
## Preview
https://github.com/aNdr3W03/Bike-Sharing-Dashboard/assets/64983961/77e55eda-49d4-47c5-8486-7a9086ed3eb1
## Description
This project is part of the bike sharing data analysis project to analyze the Bike Sharing Dataset. The results of the analysis are then made into the form of data visualization into an interactive dashboard.
## Directory
- `/assets`: stores image and video assets used in this project
- `/dashboard`: contains the file `func.py` which stores the functions needed by the dashboard
- `dataset`: stores data used in the data analysis project
- `README.md`: file that provides information about this GitHub project
- `app.py`: main file to run the dashboard
- `notebook.ipynb`: interactive jupyter notebook files to analyze data
- `requirements.txt`: file that stores information about the libraries used in this project
## Installation
The steps to create your virtual environment from this project is as follows:
1. Clone this Repository
```bash
git clone https://github.com/aNdr3W03/Bike-Sharing-Dashboard.git
```
2. Create Python Virtual Environment
```bash
virtualenv venv
```
2. Activate the Environment
```bash
venv\Scripts\activate
```
4. Install All the Requirements Inside "requirements.txt"
```bash
pip install -r requirements.txt
```
5. Run the Streamlit Dashboard
```bash
streamlit run app.py
```
6. Stop the application program by `ctrl + c`.