OpenBB/website/content/platform/reference/quantitative/summary.md

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title	description	keywords
summary	Learn how to get summary statistics on time series data using Python. This documentation page provides information on the parameters and return value of the function.	summary statistics get summary statistics summary table python time series data target column

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Get Summary Statistics.

The summary that offers a snapshot of its central tendencies, variability, and distribution. This command calculates essential statistics, including mean, standard deviation, variance, and specific percentiles, to provide a detailed profile of your target column. B y examining these metrics, you gain insights into the data's overall behavior, helping to identify patterns, outliers, or anomalies. The summary table is an invaluable tool for initial data exploration, ensuring you have a solid foundation for further analysis or reporting.

Examples

from openbb import obb
# Get Summary Statistics.
stock_data = obb.equity.price.historical(symbol='TSLA', start_date='2023-01-01', provider='fmp').to_df()
obb.quantitative.summary(data=stock_data, target='close')
obb.quantitative.summary(target='close', data=[{'date': '2023-01-02', 'open': 110.0, 'high': 120.0, 'low': 100.0, 'close': 115.0, 'volume': 10000.0}, {'date': '2023-01-03', 'open': 165.0, 'high': 180.0, 'low': 150.0, 'close': 172.5, 'volume': 15000.0}, {'date': '2023-01-04', 'open': 146.67, 'high': 160.0, 'low': 133.33, 'close': 153.33, 'volume': 13333.33}, {'date': '2023-01-05', 'open': 137.5, 'high': 150.0, 'low': 125.0, 'close': 143.75, 'volume': 12500.0}, {'date': '2023-01-06', 'open': 132.0, 'high': 144.0, 'low': 120.0, 'close': 138.0, 'volume': 12000.0}])

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Parameters

Name	Type	Description	Default	Optional
data	List[Data]	Time series data.		False
target	str	Target column name.		False

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Returns

OBBject
    results : SummaryModel
        Summary table.