This paper aims to present the possibilities for creating maps in the programming language R. Even though R is primarily developed as a statistical program, its application in the area of mapping and spatial statistics is becoming frequent and highly relevant. Many R packages make the mapping process easier and user-friendly, and this paper presents the most commonly used ones: “leaflet”, “ggplot2” and “ggmap”. The selection of the R package depends on the user’s proficiency in R programming but also depends on the visual quality of the map the user wants to gain. Based on the questionnaire conducted in this research, the paper recommends application of the “leaflet” package for the beginners, the “ggplot2” package for medium proficient use...
Scripting cartographic technique is a new method of geospatial data visualization – especially with ...
We present GeoXp, an R package implementing interactive graphics for exploratory spatial data analys...
R is a language similar to S for statistical data analysis, based on modern programming concepts a...
This book provides an introduction to the use of R for spatial statistical analysis, geocomputation ...
The main purpose of this article is to present the use of R programming language in cartographic vis...
R is a powerful and increasingly popular programming language with strong graphical and presentation...
Cartogram drawing is a technique for showing geography-related statistical information, such as demo...
R programming with map data interaction is another research area for data scientists due to high dat...
We all love maps. Like many, I grew up with the rich tapestry of Ordnance Survey landranger maps. Th...
This document constitutes the manual for the course on Introduction to spatial statistics with R of ...
This tutorial is an introduction to spatial data in R and map making with R's `base' graphics and th...
Governments and statistical agencies often make available area-level data on a number of topics (mor...
This book is intended for anyone who wants to learn how to efficiently analyze geospatial data with ...
Thematic maps show spatial distributions. The theme refers to the phenomena that is shown, which is ...
The cartography package allows various cartographic representations such as proportional symbols, ch...
Scripting cartographic technique is a new method of geospatial data visualization – especially with ...
We present GeoXp, an R package implementing interactive graphics for exploratory spatial data analys...
R is a language similar to S for statistical data analysis, based on modern programming concepts a...
This book provides an introduction to the use of R for spatial statistical analysis, geocomputation ...
The main purpose of this article is to present the use of R programming language in cartographic vis...
R is a powerful and increasingly popular programming language with strong graphical and presentation...
Cartogram drawing is a technique for showing geography-related statistical information, such as demo...
R programming with map data interaction is another research area for data scientists due to high dat...
We all love maps. Like many, I grew up with the rich tapestry of Ordnance Survey landranger maps. Th...
This document constitutes the manual for the course on Introduction to spatial statistics with R of ...
This tutorial is an introduction to spatial data in R and map making with R's `base' graphics and th...
Governments and statistical agencies often make available area-level data on a number of topics (mor...
This book is intended for anyone who wants to learn how to efficiently analyze geospatial data with ...
Thematic maps show spatial distributions. The theme refers to the phenomena that is shown, which is ...
The cartography package allows various cartographic representations such as proportional symbols, ch...
Scripting cartographic technique is a new method of geospatial data visualization – especially with ...
We present GeoXp, an R package implementing interactive graphics for exploratory spatial data analys...
R is a language similar to S for statistical data analysis, based on modern programming concepts a...