In R-Lab#2 we realized a Shinyapp that shows the earthquakes evolution over the Bove-Vettore fault. Here report, code, slides and app!
R has become an essential tool in oceanography and marine ecology. For instance, R is specifically used to read, process and represent in situ oceanographic data and to manage satellite data in order to produce high temporal and spatial resolution maps useful to synoptically explore and monitoring vast areas of the world oceans. In this post we briefly describe a practical use of R in conjunction with satellite data to identify marine bioregions of the Labrador Sea with different patters in the phytoplankton seasonal cycle.
Detect sentinel values, recode factor variables, replace missing values: a tutorial on various steps in data preparation using R.
Have you ever tried to set multiple legends for the same aesthetics of a ggplot graph? Here you will discover how to do it
In the R environment, different packages to draw maps are available. I lost the count by now; surely, sp and ggmap deserve consideration. Despite the great availability of R functions dedicated to this topic, in the past, when I needed to draw a very basic map of Italy with regions marked with different colours (namely a choropleth map), I had a bit of difficulties.
Some time ago, I was contacted from guys at Packt Publishing. Their just published the Building Interactive Graphs with ggplot2 and Shiny online course and they ask me my (humble) opinion.
In Part 1 of this series we moved the first steps into building our Sales Dashboard in R. In this Part 2 we explore additional ways to display sales related data.
If you haven't read Part 1, it is highly recommended that you do so first because we will build on what was covered there.
In a previous post on my personal blog about creating Pivot Tables in R with melt and cast we covered a simple way to generate sales reports and summary tables from a data set consisting of orders. It is often said that a picture is worth 1000 words, so in this series of posts we will focus on how to create visual representations and summaries of the same data.
Our graphical library of choice for the job will be ggplot2 (what else?), even though we are mostly going to use it in its simplest format, which is through qplot. I have written other posts on ggplot2 which you may want to also read.
This is the third article of the Maps in R series. After having shown how to draw a map without placing data on it and how to plot point data on a map, in this installment the creation of a choropleth map will be presented.
A choropleth map is a thematic map featuring regions colored or shaded according to the value assumed by the variable of interest in that particular region.