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##Documentation of dataset
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This dataset contains historical stock price data for a financial asset, including information on opening price, daily highs, lows, closing prices, and trading volume over time. It is well-suited for time series analysis, price modeling, and volatility studies.
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#Dataset features,values and transformation
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Date:
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Description: The specific date of the recorded data.
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Values: Date in the format YYYY-MM-DD
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Transformation: Converted to seconds since epoch to accomodate machine learning models
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Open:
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Description: The price of Bitcoin at the beginning of the trading day or the first recorded price.
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Values: Numeric values representing Bitcoin's price in USD.
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Transformation:None
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Mean
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23241.696396132284
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Standard deviation
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19766.306933435302
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Minimum
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775.177978515625
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25th percentile
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7277.4925537109375
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Median
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16601.78515625
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75th percentile
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37470.646484375
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Maximum
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73079.37
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High:
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Description: The highest price of Bitcoin during the trading day.
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Values: Numeric values representing Bitcoin's highest price in USD.
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Transformation:None
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Mean
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23767.721451924786
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Standard deviation
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20199.763572512365
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Minimum
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823.3070068359375
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25th percentile
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7435.2149658203125
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Median
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16804.05859375
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75th percentile
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38601.0966796875
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Maximum
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73750.0703125
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Low:
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Description: The lowest price of Bitcoin during the trading day.
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Values: Numeric values representing Bitcoin's lowest price in USD.
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Transformation:None
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Mean
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22681.085905475913
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Standard deviation
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19290.27829954119
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Minimum
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755.7559814453125
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25th percentile
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7113.698974609375
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Median
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16284.66357421875
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75th percentile
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36421.3798828125
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Maximum
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71334.093
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Close:
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Description: The price of Bitcoin at the end of the trading day or the last recorded price.
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Values: Numeric values representing Bitcoin's closing price in USD.
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Transformation:None
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Mean
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23262.039341613166
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Standard deviation
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19773.829051568417
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Minimum
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777.7570190429688
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25th percentile
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7277.7904052734375
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Median
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16603.525390625
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75th percentile
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37493.4990234375
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Maximum
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Adj Close (Adjusted Close):
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Description: The closing price adjusted for any corporate actions, such as stock splits or dividends. In the case of cryptocurrencies, this may include adjustments due to market factors.
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Values: Numeric values representing Bitcoin’s adjusted closing price.
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Transformation: None
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Mean
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23262.039341613166
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Standard deviation
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19773.829051568417
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Minimum
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777.7570190429688
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25th percentile
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7277.7904052734375
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Median
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16603.525390625
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75th percentile
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37493.4990234375
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Maximum
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73083.5
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Volume:
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Description: The total volume of Bitcoin traded during the day.
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Values: Numeric values representing the volume of Bitcoin traded.
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Transformation:None
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Mean
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22879032456.019394
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Standard deviation
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18889171723.565956
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Minimum
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60851700.0
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25th percentile
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7730409119.25
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Median
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20265863393.5
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75th percentile
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32520370302.75
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Maximum
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35096794
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#Target Variable
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Close-Predicting the Close price for future days can be useful for traders aiming to anticipate market moves. This is a typical regression problem where the goal is to predict the price value
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