https://github.com/wiqilee/crypto-sentiment-dashboard
Real-time crypto news sentiment dashboard using NewsAPI + VADER. Analyze BTC/ETH/SOL trends, visualize with Plotly/Matplotlib, export PDF.
https://github.com/wiqilee/crypto-sentiment-dashboard
bitcoin coingecko cryptocurrency dashboard data-visualization ethereum matplotlib newsapi pdf plotly python reportlab sentiment-analysis snscrape solana streamlit time-series vader vader-sentiment-analysis
Last synced: 11 days ago
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Real-time crypto news sentiment dashboard using NewsAPI + VADER. Analyze BTC/ETH/SOL trends, visualize with Plotly/Matplotlib, export PDF.
- Host: GitHub
- URL: https://github.com/wiqilee/crypto-sentiment-dashboard
- Owner: wiqilee
- License: mit
- Created: 2025-08-10T15:15:10.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-08-10T16:02:19.000Z (12 months ago)
- Last Synced: 2026-07-28T09:40:05.028Z (11 days ago)
- Topics: bitcoin, coingecko, cryptocurrency, dashboard, data-visualization, ethereum, matplotlib, newsapi, pdf, plotly, python, reportlab, sentiment-analysis, snscrape, solana, streamlit, time-series, vader, vader-sentiment-analysis
- Language: Python
- Homepage:
- Size: 22.5 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Crypto Sentiment Dashboard
[](https://github.com/)
A Streamlit dashboard for analyzing crypto news sentiment (BTC / ETH / SOL / OTHER) using VADER.
It includes interactive charts (Plotly), export-ready PNGs (RGB-safe), and a print-quality PDF report (ReportLab).
> **Disclaimer:** This project is for research and monitoring purposes only. It is **not** financial advice.
---
## ✨ Features
- **Interactive charts** — Source & label bar charts, daily time-series, and correlation heatmap.
- **Crypto domain insights** — Auto-generated summary, bullet-point analysis, recommendations, and conclusion.
- **Export-ready images** — Large-canvas PNGs with generous margins, **forced RGB** to avoid disappearing lines in PDFs.
- **One-click PDF** — A neatly paginated report with all charts and summary sections.
- **Powerful filters** — Label, source, and UTC date range.
- **Pandas compatibility** — Hides table index with a safe fallback for older pandas versions.
---
## 🚀 Quick start
```bash
# 1) (optional) create a virtual environment
python -m venv .venv
# activate it:
# Windows: .venv\Scripts\activate
# macOS/Linux: source .venv/bin/activate
# 2) install dependencies
pip install -r requirements.txt
# 3) run the app
streamlit run streamlit_app.py
```
The app reads data from `data/news_raw.csv`.
---
## 📦 Requirements
- Python **3.10+** (recommended)
- `streamlit`, `pandas`, `numpy`
- `plotly`, `matplotlib`
- `kaleido` (PNG export backend for Plotly)
- `reportlab`, `Pillow` (PDF builder and image backend)
All pinned in `requirements.txt`.
---
## 🗂️ Data schema
The loader (`sentiment.py`) normalizes your columns automatically. Minimum required:
- `publishedAt` / `published` / `date` → normalized to `publishedat` (UTC timezone)
- `source` — outlet name/domain
- `compound` — VADER score in `[-1, +1]`
Optional:
- `channel`, `title`, `description`, `url`, `label` (if `label` is missing, it is inferred from text: **BTC/ETH/SOL**, else **OTHER**)
**Example row:**
```csv
publishedAt,source,compound,title,url,label
2025-08-01T10:30:00Z,CoinDesk,0.21,"BTC breaks range","https://example.com/article",BTC
```
> Tip: If your dataset is large or sensitive, keep it out of your repo and list `data/*.csv` in `.gitignore`.
---
## 📊 Charts & PDF exports
When you click **Build PDF report** in the UI, the app:
1. Saves high-resolution PNGs for each chart with large margins so labels never get cropped.
2. **Forces RGB** (removes alpha) on the PNGs to prevent thin lines from disappearing in PDFs.
3. Assembles a polished, paginated PDF using ReportLab — one chart per page, plus summaries.
**About the time-series edges**
The PDF version uses a small time padding by default to avoid edge clipping. You can switch to fully edge-to-edge by editing the `timeseries_by_label(..., theme_for_pdf=True)` x-axis range in `streamlit_app.py`.
---
## 🧱 Project structure
```
.
├─ streamlit_app.py # Streamlit UI (Plotly + PDF trigger)
├─ sentiment.py # Data loader, domain analysis, print-safe charts (matplotlib), PDF builder
├─ requirements.txt
├─ data/
│ └─ news_raw.csv # Your dataset (kept local by default)
├─ charts/ # Generated PNGs (auto-created)
└─ LICENSE # MIT © 2025–present wiqilee
```
---
## ⚙️ Configuration
Adjust label colors/order in both modules if desired:
```python
LABEL_COLORS = {"BTC": "#22c55e", "ETH": "#ffffff", "SOL": "#fde047", "OTHER": "#94a3b8"}
LABEL_ORDER = ["BTC", "ETH", "SOL", "OTHER"]
```
---
## 🛠️ Troubleshooting
- **`kaleido` export error**
Ensure `kaleido==0.2.1` is installed:
```bash
pip install --upgrade kaleido
```
- **Time-series lines missing in PDFs**
Already handled by forcing RGB on exported PNGs. Make sure `Pillow` is installed.
- **Table index won’t hide (old pandas)**
The app falls back from `styler.hide_index()` to `styler.hide(axis="index")` automatically.
---
## 🗺️ Roadmap
- Automated news ingestion
- Alternative sentiment models beyond VADER
- One-click deploy to Streamlit Community Cloud
---
## 🤝 Contributing
Contributions are welcome! Please open an issue or submit a pull request.
Make sure your PR includes a clear description and, when possible, screenshots of UI changes.
---
## 📜 License
**MIT** © 2025–present **wiqilee** — see [`LICENSE`](./LICENSE) for details.