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This article presents Rilostat and SMART, two statistical tools developed by the Department of Statistics of the International Labour Organization (ILO) to facilitate the user interaction with ILOSTAT, the largest repository of labour-related indica-tors. The package Rilostat allows data users around the world to access, extract and manipulate information from ILOSTAT. This document presents a description of the package, including detailed explanations of all its functionalities, examples of reproducible data visualization and a Principal Component Analysis application car-ried out using information extracted with Rilostat from the Sustainable Development Goals (SDGs) collection available in the database. The Statistics Metadata-driven Analysis and Reporting Tool (SMART) allows National Statistical Offices world-wide to easily generate and automate the production of analytical reports (such as national SDG reporting) defined by means of an SDMX Data Structure Definition (DSD), either from processing micro-level data or from aggregated data by means of transcoding. It is a hybrid application that employs the .NET framework to build the user interface and R as the computational and reporting engine. These two R-based tools for ILOSTAT take advantage of all the benefits of the R software to give ILOSTAT data users simplified access to what they need.

This article presents Rilostat and SMART, two statistical tools developed by the Department of Statistics of the International Labour Organization (ILO) to facilitate the user interaction with ILOSTAT, the largest repository of labour-related indica-tors. The package Rilostat allows data users around the world to access, extract and manipulate information from ILOSTAT. This document presents a description of the package, including detailed explanations of all its functionalities, examples of reproducible data visualization and a Principal Component Analysis application car-ried out using information extracted with Rilostat from the Sustainable Development Goals (SDGs) collection available in the database. The Statistics Metadata-driven Analysis and Reporting Tool (SMART) allows National Statistical Offices world-wide to easily generate and automate the production of analytical reports (such as national SDG reporting) defined by means of an SDMX Data Structure Definition (DSD), either from processing micro-level data or from aggregated data by means of transcoding. It is a hybrid application that employs the .NET framework to build the user interface and R as the computational and reporting engine. These two R-based tools for ILOSTAT take advantage of all the benefits of the R software to give ILOSTAT data users simplified access to what they need. [ABSTRACT FROM AUTHOR]

The focus of this paper is on identification of typical graphical user interface (GUI) programming concerns. As opposed to some other proposals available in the literature that indicate GUI programming concerns by simple intuition, we have conducted a systematic empirical analysis to derive our proposal. It included an analysis of an existing application programming interface (API), its use in industrial projects, and an analysis of the requirements and issues reported during software maintenance. In addition, we have evaluated more than 50 GUI frameworks and APIs and proved usefulness and generality of our classification of concerns. As an additional proof of applicability of the proposed classification, we have refactored the inheritance hierarchy of the selected GUI API using concern-oriented interfaces. We have implemented a supporting tool that complements the developed API and supports its concern-oriented use. The evaluation of the refactored API showed positive effects on API usability. [ABSTRACT FROM AUTHOR]

This paper puts forward the design, programming and application of innovative educational software, 'Aura' made using Python and PyQt Python bindings. The research paper presents a new concept of using a single tool to relate between syntaxes of various programming languages and algorithms. It radically increases their understanding and retaining capacity, since they can correlate between many programming languages. The software is a totally unorthodox attempt towards helping students who have their first tryst with programming languages. The application is designed to help students understand how algorithms work and thus, help them in learning multiple programming languages on a single platform using an interactive graphical user interface. This paper elucidates how using Python and PyQt bindings, a comprehensive feature rich application, that implements an interactive algorithm building technique, a web browser, multiple programming language framework, a code generator and a real time code sharing hub be embedded into a single interface. And also explains, that using Python as building tool, it requires much less coding than conventional feature rich applications coded in other programming languages, and at the same time does not compromise on stability, inter-operability and robustness of the application. [ABSTRACT FROM AUTHOR]