@misc{Brzezińska_Justyna_Visualization_2018,
 author={Brzezińska, Justyna},
 identifier={DOI: 10.15611/eada.2018.2.01},
 year={2018},
 rights={Pewne prawa zastrzeżone na rzecz Autorów i Wydawcy},
 publisher={Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu},
 description={Econometrics = Ekonometria, 2018, Vol. 22, No. 2, s. 9-19},
 language={eng},
 abstract={Visualization in research process plays a crucial role. There are several advanced plots for visualizing categorical data, such as mosaic, association, double-decker, sieve or fourfold plot that are based on the graphical presentation of residuals in a contingency table. In this paper we present new methods for visualizing categorical data such as rmb, fluctile and scpcp plot available in extracat package in R. This package provides a well-structured representation of categorical data and allows for a detailed presentation of the relationship between categories in terms of proportions. We describe rmb, fluctile and cpcp. Those plots are based on the concept of multiple bar charts, a fluctuation diagram from a multidimensional table and parallel coordinates respectively. Such plots are mostly used for a visualization of a contingency table or a data frame; they can also be used for exploratory analysis and allows for a graphical presentation even for a high number of variables [Pilhöfer, Unwin 2013]. All the calculations and plots are obtained using R software},
 title={Visualization of categorical data using extracat package in R},
 type={artykuł},
 keywords={categorical data, cpcp plot, rmb plot, fluctile plot, R software, wizualizacja, wykres scpcp, wykres rmb, funkcja fluktuacji, program R},
}