summary

Get descriptive summary statistics for a data series.

Computes the count, central tendency, dispersion, and quartile distribution of the target column. Provides a concise profile of the data for initial exploration and reporting.

Examples

from openbb import obb
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}])

Parameters

• standard

data: Data | DataFrame | Series | dict | list | list[DataFrame] | list[Data] | list[Series] | ndarray
Input dataset.

target: str
Name of the column to analyze.

---

Returns

results: SummaryData

Serializable results.

provider: str

Provider name.

warnings: Optional[list[Warning_]]

List of warnings.

chart: Optional[Chart]

Chart object.

extra: dict[str, Any]

Extra info.

---

Data

• standard

count: int
Number of observations.

mean: float
Arithmetic mean.

std: float
Sample standard deviation.

var: float
Sample variance.

min: float
Minimum value.

p25: float
25th percentile.

p50: float
50th percentile (median).

p75: float
75th percentile.

max: float
Maximum value.