**Due to a strike, MilanoR meeting postponed to June 4**

A causa di uno sciopero, il meeting MilanoR previsto per il 30 maggio è stato rinviato al 4 giugno.

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.

Dear R users,

the May 2014 public training course schedule for Milano (Italy) based courses is as follows:

Web Applications with R and Shiny | May 15, 2014 |

Reports in R with RStudio | May 16, 2014 |

Basic R Programming | May 22, 2014 |

Data Visualization with R | May 23, 2014 |

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.

R is a powerful system for statistical analysis and data visualization. However, it’s not exactly user-friendly for data storage, so, still for several time your data will be archived using Excel, SPSS or similar programs.

How to open into R a file stored using the SPSS (.sav) format? There are some packages as `foreign`

which allow to perform this operation. The package foreign is already present in the base distribution of R system and you just need to activate it using the function `library()`

.

My previous article shows an example in which data analysis requires a structured framework with R and OOP. In order to explain how to build the framework this article describes how to do that in more detail.

Using OOP means creating new data structures and defining their methods that are functions performing a specific tasks on the object. Defining a new data structure requires creating a new class and this articles shows how to create it through S4 R classes.

**"Statistical Models with R" Course**

March 27 and 28, 2014

**Course description**

This two-day course shows a wide variety of statistical models with R ranging from Linear Models (LM) to Generalized Linear Models (GLM) modelling, in order to provide a broad overview of statistical linear models with R.

The course will follow a step-by-step approach from simplest to more complex models to illustrate the R capabilities on modeling. Some theoretical introductions are given in course materials.

Brief introductions to modeling with Mixed Effects, GAM, Neural Networks and Trees are also provided.

**"A short introduction to R" Course**

March 26, 2014

**Course description**

This one-day course aims to provide an overview of the basic R environment and its applications. This course is intended as a starting point for any future development with R. At the end of the course, you will be able to gain awareness of the basic R language, importing data and manipulate data using R.