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prathmesh2507 / repository
Interactive Global Stock Market Analytics Dashboard built using Python, YFinance, Pandas, Streamlit, and Plotly. Analyze 20+ countries and 400+ top stocks with advanced visualizations and financial insights.
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Analyze market movements, explore stock performance, compare global markets, and generate actionable insights through an interactive financial dashboard.
Financial markets generate enormous amounts of data daily, making it difficult for investors and analysts to quickly identify trends, compare markets, and understand stock behavior.
This project builds an interactive stock intelligence platform that transforms raw stock market data into meaningful insights through:
The goal is not just visualization — but helping users understand what is happening in the market and why.
Supports stocks across:
🇺🇸 USA
🇮🇳 India
🇬🇧 UK
🇨🇦 Canada
🇯🇵 Japan
🇩🇪 Germany
🇫🇷 France
🇨🇳 China
🇭🇰 Hong Kong
🇸🇬 Singapore
🇰🇷 South Korea
🇸🇦 Saudi Arabia
🇦🇺 Australia
🇧🇷 Brazil
🇹🇼 Taiwan
🇳🇱 Netherlands
🇨🇭 Switzerland
🇸🇪 Sweden
🇮🇹 Italy
🇪🇸 Spain
This dashboard helps answer:
Global-Stock-Intelligence-Dashboard/
│
├── data/
│ ├── AUSTRALIA_Final.csv
│ ├── Brazil_Final.csv
│ ├── CANADA_Final.csv
│ ├── China_Final.csv
│ ├── ...
│ └── USA_Final.csv
│
├── notebook/
│ └── stocks.ipynb
│
├── app.py
├── final_data.csv
├── requirements.txt
├── README.md
│
└── screenshots
| Attribute | Details |
|---|---|
| Countries Covered | 20 |
| Data Source | Yahoo Finance |
| Features | OHLCV + Metadata |
| Historical Data | Multi-country |
| Format | CSV |
| Columns | Date, Open, High, Low, Close, Volume, Stock_Name, Ticker, Country |
| Technology | Purpose |
|---|---|
| Python | Core Development |
| Pandas | Data Processing |
| NumPy | Numerical Analysis |
| Streamlit | Dashboard Framework |
| Plotly | Interactive Visualizations |
| YFinance | Stock Data Collection |
| Jupyter Notebook | Research & EDA |
| CSS | Custom UI |
Clone repository:
git clone https://github.com/prathmesh2507/Global-Stock-Intelligence-Dashboard.git
Move into folder:
cd World-Stock-Analytics
Install dependencies:
pip install -r requirements.txt
Run dashboard:
python -m streamlit run app.py
Prathmesh Bhoyar
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