https://github.com/teonghan/stat_quickie
StatQuickie is a lightning-fast, no-nonsense stats explorer that makes data analysis simple, visual, and accessible for everyone. Upload your CSV or Excel file and instantly get layman-friendly summaries, interactive charts, and powerful statistical insights—all without writing a single line of code. Powered by Streamlit.
https://github.com/teonghan/stat_quickie
data-analysis data-visualization python statistics streamlit
Last synced: about 5 hours ago
JSON representation
StatQuickie is a lightning-fast, no-nonsense stats explorer that makes data analysis simple, visual, and accessible for everyone. Upload your CSV or Excel file and instantly get layman-friendly summaries, interactive charts, and powerful statistical insights—all without writing a single line of code. Powered by Streamlit.
- Host: GitHub
- URL: https://github.com/teonghan/stat_quickie
- Owner: teonghan
- License: mit
- Created: 2025-05-27T05:37:19.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-08-07T05:20:16.000Z (11 months ago)
- Last Synced: 2025-08-07T05:28:47.412Z (11 months ago)
- Topics: data-analysis, data-visualization, python, statistics, streamlit
- Language: Python
- Homepage:
- Size: 490 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 📊 StatQuickie: Your Fast Lane to Data Insights!
[](https://statquickie.streamlit.app/)
[](https://streamlit.io/)
Say hello to **StatQuickie** — the playful, no-nonsense stats explorer that helps you *understand your data* in record time.
Upload a file, sip your coffee, and boom — insight! ☕📈
👉 **Try it live:** [https://statquickie.streamlit.app](https://statquickie.streamlit.app)
---
## 🚀 What’s Inside?
- 🗂 Upload CSV or Excel files
- 🔍 Auto-detects numbers, categories, and dates
- 🧠 Layman-friendly summaries (e.g., “tightly clustered” vs “widely spread”)
- 📊 Visualize with Plotly + Matplotlib (histograms, KDE, ECDFs, etc.)
- 🧪 Run t-tests, fit regression lines, get R² and MSE instantly
- 🎛 Interactive UI with Streamlit — no code needed!
---
## 🛠 Installation
### Option 1: One-Click macOS Installer
```bash
bash installer-macos-universal.sh
```
This will:
- Detect your Mac architecture (Intel or Apple Silicon)
- Install Miniforge (if needed)
- Create the `statquickie` environment
- Add Desktop shortcut to launch the app【93†source】
---
### Option 2: One-Click Windows Installer
```powershell
Right-click → Run with PowerShell → installer-windows.ps1
```
This will:
- Detect Anaconda/Miniconda installation
- Create or update `statquickie` conda environment using `__environment__.yml`
- Create a launcher script and desktop shortcut
- Generate an uninstaller for cleanup
> 💡 **Note:** Ensure Conda is installed before running.
---
### Option 3: Manual Setup
```bash
git clone https://github.com/your-username/statquickie.git
cd statquickie
pip install -r requirements.txt
streamlit run app.py
```
---
## 🔧 Dependencies
From `requirements.txt`:
- `streamlit`, `pandas`, `numpy`, `matplotlib`, `plotly`, `openpyxl`, `xlrd`
- `scikit-learn`, `scipy`, `lightgbm`【95†source】
---
## 🎯 Why Use StatQuickie?
Because not everyone has time to write Python scripts or decipher p-values.
StatQuickie lets you:
- Get the story behind the numbers
- Show off visual insights in seconds
- Wow your colleagues (or your future self)
Whether you're a data newbie or seasoned analyst, StatQuickie makes stats feel less... staticky.
---
## 🤝 Contribute
Pull requests welcome! Open an issue, suggest features, or drop by with a virtual high-five ✋
Let’s make stats less scary, together.
---
## 📄 License
MIT License — do what you want, just don’t blame us if your boss loves it too much.
---
## 🙌 Acknowledgements
Thanks to [OpenAI's ChatGPT](https://chat.openai.com/) for helping brainstorm, draft, and polish this README — and making documentation (and stats) a lot more fun.