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numeric_stats

numeric_stats ¤

NumericStatistics ¤

NumericStatistics(
    dataframe: DataFrame, column_name: str = "systime"
)

Bases: Base

Provides class methods to calculate statistics on numeric columns in a pandas DataFrame.

column_mean classmethod ¤

column_mean(
    dataframe: DataFrame, column_name: str
) -> float

Calculate the mean of a specified column.

column_median classmethod ¤

column_median(
    dataframe: DataFrame, column_name: str
) -> float

Calculate the median of a specified column.

column_std classmethod ¤

column_std(dataframe: DataFrame, column_name: str) -> float

Calculate the standard deviation of a specified column.

column_variance classmethod ¤

column_variance(
    dataframe: DataFrame, column_name: str
) -> float

Calculate the variance of a specified column.

column_min classmethod ¤

column_min(dataframe: DataFrame, column_name: str) -> float

Calculate the minimum value of a specified column.

column_max classmethod ¤

column_max(dataframe: DataFrame, column_name: str) -> float

Calculate the maximum value of a specified column.

column_sum classmethod ¤

column_sum(dataframe: DataFrame, column_name: str) -> float

Calculate the sum of a specified column.

column_kurtosis classmethod ¤

column_kurtosis(
    dataframe: DataFrame, column_name: str
) -> float

Calculate the kurtosis of a specified column.

column_skewness classmethod ¤

column_skewness(
    dataframe: DataFrame, column_name: str
) -> float

Calculate the skewness of a specified column.

column_quantile classmethod ¤

column_quantile(
    dataframe: DataFrame, column_name: str, quantile: float
) -> float

Calculate a specific quantile of the column.

column_iqr classmethod ¤

column_iqr(dataframe: DataFrame, column_name: str) -> float

Calculate the interquartile range of the column.

column_range classmethod ¤

column_range(
    dataframe: DataFrame, column_name: str
) -> float

Calculate the range of the column.

column_mad classmethod ¤

column_mad(dataframe: DataFrame, column_name: str) -> float

Calculate the mean absolute deviation of the column.

coefficient_of_variation classmethod ¤

coefficient_of_variation(
    dataframe: DataFrame, column_name: str
) -> float

Calculate the coefficient of variation of the column.

standard_error_mean classmethod ¤

standard_error_mean(
    dataframe: DataFrame, column_name: str
) -> float

Calculate the standard error of the mean for the column.

describe classmethod ¤

describe(dataframe: DataFrame) -> pd.DataFrame

Provide a statistical summary for numeric columns in the DataFrame.

summary_as_dict classmethod ¤

summary_as_dict(
    dataframe: DataFrame, column_name: str
) -> Dict[str, Union[float, int]]

Returns a dictionary with comprehensive numeric statistics for the specified column.

summary_as_dataframe classmethod ¤

summary_as_dataframe(
    dataframe: DataFrame, column_name: str
) -> pd.DataFrame

Returns a DataFrame with comprehensive numeric statistics for the specified column.