ineqpy.grouped.inequality

inequality module.

Module Contents

Functions

atkinson_group([data, income, weights, group, e])

Calculate atkinson index.

ineqpy.grouped.inequality.atkinson_group(data: pandas.DataFrame = None, income: str | pandas.DataFrame | numpy.ndarray = None, weights: str | pandas.DataFrame | numpy.ndarray = None, group: str | pandas.DataFrame | numpy.ndarray = None, e: float = 0.5)

Calculate atkinson index.

The Atkinson index (also known as the Atkinson measure or Atkinson grouped measure) is a measure of income grouped developed by British economist Anthony Barnes Atkinson. The measure is useful in determining which end of the distribution contributed most to the observed grouped.The index is subgroup decomposable. This means that overall grouped in the population can be computed as the sum of the corresponding Atkinson indices within each group, and the Atkinson index of the group mean incomes.

Parameters:

incomestr or np.array

Income variable, you can pass name of variable in df or array-like

weightsstr or np.array

probability or weights, you can pass name of variable in df or array-like

groupsstr or np.array

stratum, name of stratum in df or array-like

eint, optional

Value of epsilon parameter

datapd.DataFrame, optional

DataFrame that’s contains the previous data.

Returns:

atkinson_by_groupfloat