Have you ever tried to set multiple legends for the same aesthetics of a ggplot graph? Here you will discover how to do it
Today I woke up for the first time in Aalborg. My colleague Enrico, who yesterday wrote the first post about this expedition, and I left from the hotel, walked through an underpass and came out in a wonderful park! In the end of this park there is the Aalborg Kongres & Kultur Center, the conference venue.
In these days, I was talking about an R package I developed with a colleague. He used several times the word library to refer to the R package. So, I realized that many R users do not know that package and library are not synonymous when referring to R.
The "Writing R Extensions" manual is clear: "A package is not a library", although the same manual admits "this is a persistent mis-usage".
A week ago, my boss at Quantide, Andrea Spanò, published Ramarro. Ramarro is a free interactive web based book (i.e. a web-book) about advanced R programming. The book would help R users to become proficient R developers. Target of the book are both R users and IT specialists that should deals with R users.
I discovered Plotly some days ago, and I was fascinated by it.
What is Plotly?
Plotly is a service for creating and sharing data visualizations that also offers statistical analysis tools plus a robust API, the ability to graph custom functions and a built-in Python shell. Among its APIs, there is the R one: Plotly interactive visualization can be created directly from R.
Many people still save their data into Microsoft Excel files. This is an unhappy choice for many reasons but many was already written about this topic. Furthermore, unfortunately Excel become a de facto standard in many business environment and this routine seems to be difficult to strike out.
Many solutions have been implemented to read Excel files from R: each one has advantages and disadvantages, so an universal solution is not available. Get an overview of all the solutions, allows the choice of the best solution case-by-case.
Nowadays, routinary operations on files, such as renaming or copying, are performed with some mouse clicks. Sometimes, it is useful perform this operations in batch. Linux users perform this operations through the shell. Also Windows users can use the shell, but there are also a lot of utilities that simplify these operations.
Why someone should use R to copy or rename a (lot of) file(s)?