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https://github.com/bratergit/lastchancehackertoberfest
In the final hours of hacktoberfest 2024 your last chance to get a tee
https://github.com/bratergit/lastchancehackertoberfest
hacktoberfest hacktoberfest-accepted hacktoberfest2024 numpy pandas python3 streamlit
Last synced: 16 days ago
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In the final hours of hacktoberfest 2024 your last chance to get a tee
- Host: GitHub
- URL: https://github.com/bratergit/lastchancehackertoberfest
- Owner: bratergit
- Created: 2024-10-28T08:33:52.000Z (19 days ago)
- Default Branch: main
- Last Pushed: 2024-10-28T10:50:11.000Z (19 days ago)
- Last Synced: 2024-10-28T10:50:44.681Z (19 days ago)
- Topics: hacktoberfest, hacktoberfest-accepted, hacktoberfest2024, numpy, pandas, python3, streamlit
- Language: Python
- Homepage:
- Size: 5.86 KB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 10
-
Metadata Files:
- Readme: README.md
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README
# Last Chance Hacktoberfest 2024 ππ
Welcome to **Last Chance Hacktoberfest 2024**! π This repository was created for those who still want to participate in Hacktoberfest 2024 and contribute with exciting tasks in the areas of **stocks**, **graphs**, and **data analytics**. π
## π Objectives
Hacktoberfest is a celebration of open source during the month of October. We aim to encourage and empower developers of all levels to contribute and learn through practical and fun tasks. Here you will have the chance to:
- **Contribute to ongoing projects**
- **Learn valuable skills** such as data visualization, automation, and data manipulation
- **Receive feedback** to improve your coding skills## π Repository Structure
This repository is divided into three main categories:
1. **Stocks**
- Contribute to tasks related to process automation, API integrations, or market analysis involving stocks and financial data.
- **Suggested tasks**: Automating stock market data collection, API integrations with stock exchanges, creating real-time stock dashboards.2. **Graphs**
- Create or improve data visualizations using libraries like Matplotlib, Plotly, or D3.js.
- **Suggested tasks**: Build interactive graphs, dashboards, or time series visualizations.3. **Analytics**
- Provide scripts or notebooks for data analysis using Python (Pandas, NumPy) or R.
- **Suggested tasks**: Exploratory data analysis, building predictive models, data cleaning and transformation.Each contribution should be made within its respective directory:
- `stocks/` for stock-related contributions
- `graphs/` for graphical or data visualization tasks
- `analytics/` for data analysis tasksFor each contribution, create a **sub-directory** within the appropriate folder and include your code there, along with a `README.md` file that explains what the contribution does, how to use it, and any necessary setup instructions.
### Example Structure:
/stocks/my-stock-analysis/my_stock_analysis.py
README.md/graphs/interactive-graph-visualization/
graph_visualization.py
README.md/analytics/data-analysis-on-customer-dataset/
customer_analysis.ipynb
README.md## π― How to Contribute
1. Fork this repository.
2. Clone the repository to your local machine:
```bash
git clone https://github.com/bratergit/lastChanceHackertoberfest.git3. Choose a task from the issues section or create your own.
4. Create a branch with the name of your task:
git checkout -b my-task
5. Add your solution in the appropriate directory: stocks/, graphs/, or analytics/.
6. Push your changes and submit a pull request (PR):
git push origin my-task
7. Open a PR on the original repository and wait for feedback.π Contribution Guidelines
PR minimum size: Contributions should be meaningful. Small typo fixes or trivial changes will not count as valid Hacktoberfest PRs.
Respect the code of conduct: Ensure the environment is inclusive and respectful.
Check existing code: Before starting a new task, see if anyone is already working on something similar.π Technologies Used
This repository uses the following technologies:Languages: Python, R, JavaScript
Graphing Tools: Matplotlib, Plotly, D3.js
Data Analysis Tools: Pandas, NumPy, SciPy
Automation: GitHub Actions, Jenkins, CircleCIπ Beginner-Friendly Challenges
If youβre new to open-source contributions, donβt worry! We have simple tasks you can start with. Look for issues labeled good first issue.
π License
This project is licensed under the MIT License. See the LICENSE file for more details.Donβt miss your last chance to participate in Hacktoberfest 2024! Letβs learn, contribute, and have fun together. If you need any help, feel free to open an issue.
π» Happy Hacking! π»π