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Income inequality is an important issue that has to be solved in order tomake progress in our society. The study of income inequality is well receivedthrough the Gini coefficient, which is used to measure degrees of inequality ingeneral. While this method is effective in several aspects, the Ginicoefficient alone inevitably overlooks minority subpopulations (e.g.occupations) which results in missing undetected patterns of inequality inminority.  In this study, the surveys of incomes and occupations from more than 12millions households across Thailand have been analyzed by using both Ginicoefficient and network densities of income domination networks to get insightregarding the degrees of general and occupational income inequality issues. Theresults show that, in agricultural provinces, there are less issues in bothtypes of inequality (low Gini coefficients and network densities), while somenon-agricultural provinces face an issue of occupational income inequality(high network densities) without any symptom of general income inequality (lowGini coefficients). Moreover, the results also illustrate the gaps of incomeinequality using estimation statistics, which not only support whether incomeinequality exists, but that we are also able to tell the magnitudes of incomegaps among occupations. These results cannot be obtained via Gini coefficientsalone. This work serves as a use case of analyzing income inequality from bothgeneral population and subpopulations perspectives that can be utilized instudies of other countries.

Occupational Income Inequality of Thailand: A Case Study of Exploratory Data Analysis beyond Gini Coefficient