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README.md
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license: cc0-1.0
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---
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license: cc0-1.0
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---
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# Intel Stock Data (1980-2024)
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This is a dataset copied from Kaggle. You can see the original dataset here: <https://www.kaggle.com/datasets/mhassansaboor/intel-stock-data-1980-2024>
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---
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**The following is the original readme of this dataset:**
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## About Dataset
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### ๐ Intel Stock Dataset (1980-2024)
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๐ This dataset contains daily stock trading data for Intel Corporation (ticker: INTC) from 1980 to 2024, sourced from Yahoo Finance. It provides a comprehensive view of Intel's stock performance over four decades, including key metrics like opening/closing prices, trading volume, dividends, and stock splits.
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---
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### ๐ Dataset Overview
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- ๐๏ธ Time Period: 1980 to 2024
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- ๐ Total Records: 11,289 rows
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- ๐ File Size: ~989.25 KB
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This dataset is ideal for financial analysis, stock trend forecasting, machine learning models, and portfolio optimization studies.
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---
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### ๐ Columns and Descriptions
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๐ท๏ธ Column | ๐ Description
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--- | ---
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๐
Date | The trading date in YYYY-MM-DD format.
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๐ Open | The opening price of Intel's stock on the given day.
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๐ High | The highest price of the stock during the trading session.
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๐ Low | The lowest price of the stock during the trading session.
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๐ Close | The closing price of the stock on the given day.
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๐ Volume | The total number of shares traded on the given day.
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๐ฐ Dividends | The dividend payouts, if applicable, on the given day.
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๐ Stock Splits | The ratio of stock splits (if applicable) on the given day (e.g., 2-for-1 split = 2.0).
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---
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### ๐ Key Features
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- Clean and Complete: No missing values across all columns.
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- Rich Historical Data: Captures Intel's stock trends and major events over the years.
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- Ready for Analysis: Ideal for time-series analysis, regression models, and financial forecasting.
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### ๐ Applications
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- ๐ Trend Analysis: Identify long-term trends and patterns in Intel's stock performance.
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- ๐ค Machine Learning: Train predictive models for stock price forecasting.
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- ๐ผ Portfolio Insights: Analyze Intel's stock as part of an investment portfolio.
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- ๐งฎ Statistical Research: Study correlations between market events and stock performance.
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---
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Feel free to dive into the dataset and unlock its potential! Let me know if you need help with analysis or visualization. ๐
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