Next session: Time series analysis, June 24th 2021 at 5PM on Zoom.

Registration to the event here.

Link to Zoom here.

You can subscribe to our emailing list on the following link: r-in-grenoble emailing list.

You can checkout our YouTube channel here.

Help us communicate

Please talk about our R group with your colleagues.

You can also print this poster and put it up somewhere at work.

Join our R working sessions in Grenoble

We organise monthly working sessions on thursdays at 5PM, at the IMAG building. Due to COVID-19 restrictions all sessions to come and until further notice will be held by ZOOM.

Please find the guidelines for these sessions:

Schedule of 2020-2021

Click on the title to see the session description

October 22, 2020
Organising exams in R
PJ-F. Coeurjolly
    Package {exams} enables creating questionnaires that combine program output, graphs, etc in an automatised and dynamic fashion. They may be exported in many different formats: html, pdf, nops and most intresting xml. Xml is compatible with moodle which allows to reproducibly generate random questions in R and create a great number of different exams and make them an online moodle exam.
November 26, 2020
Collect and use open access World Bank data to know your country + Flash talk: Contribute to the response to COVID-19
M. Rolland, B. Thiago Tomio
    Package {WDI} enables exploring 40 different datasets hosted by the World Bank. The database World Development Indicators (‘WDI’) contains 1,600 time series indicators for 217 economies and more than 40 country groups. For many series, data goes back more than 50 years. The package is very useful to explore the development of the countries. We will download and plot data together during this session.
December 17, 2020
Alternatives to Rstudio
N. Gusarov
    RStudio is the most widely used IDE designed to optimize the workflow with R language. However, there exists many alternatives designed for more specific use cases. Among the most popular, there are VS-Code, Jupyter, Atom and many others. What are the advantages they offer? Can they be more useful than RStudio?
January 14, 2021
Using UGA’s Ciment servers with R
M. Gueguen, P-A. Bouttier
    In this session we will start with a general overview of UGA (University of Grenoble) severs by P-A. Bouttier from GRICAD (Grenoble’s infrastructure for intensive computing). He will present what these servers are, what they can be used for (scientific computing, data management, etc) and the different services provided by GRICAD to the Grenoble scientific community. Then in the main part of the presentation, M. Gueguen will present in which situations you may want to use such servers and how to do so in R. The presentation will be illustrated by several examples.
February 25, 2021
Machine learning
C. Gain
    In this presentation, we will mainly focus on the supervised part of the machine learning. More specifically, we will see how to use Deep Learning in R in order to solve supervised learning task. The presentation will first introduce briefly what supervised learning is and the conceptual idea behind Deep Learning. We will then present how to use deep learning in R using the framework Keras and solving image recognition task.
March 25, 2021
Data visualisation with {ggplot2}
M. Rolland
April 29, 2021
Data manipulation with packages {dplyr} and {data.table}
P. Jedynak & M. Rolland
May 06, 2021
Version control and git for beginners
P. Jedynak, M. Rolland
    Git is a version control system whose original purpose was to help groups of developers work collaboratively on big software projects. Git manages the evolution of a set of files – called a repository – in a sane, highly structured way. Git has been re-purposed by the data science community. In addition to using it for source code, we use it to manage the motley collection of files that make up typical data analytical projects, which often consist of data, figures, reports, and, yes, source code. In this presentation aimed at beginners we will try to give you an understanding on what git is, how it is integrated in Rstudio and how it can help you make your projects more reproducible, enable you to share your code with the world and collaborate in a seamless manner. (abstract strongly inspired by the intro from
May 25, 2021
Building dashboards in R/shiny (and improve them with logs and user feedback)
M. Kaufman, N. Ricci
    The main goal of this seminar is to demonstrate how R/Shiny app developers can collect data from the visitors of their app (such as logs or feedback) to improve it. We will use as example the CaDyCo project, a dynamic and collaborative cartography project hosted by USMB and UGA.
June 24, 2021
Time series
A. Zaher
    Time series data correspond to a sequence taken at successive and equidistant points in time, and their applications include several domains in which we deal with this temporal dimension. In this session, we will give an introduction to the general process of analyzing a time series data in R, starting with the visualization through different methods and packages, then we will discuss the processing stage, and finally arrive at the modeling and forecasting step. The most relevant used packages are: tsdl for uploading time series data; zoo and xts for reading and arranging data as time series; lattice, latticeExtra for static graphics; RColorBrewer for defining color palettes; and packages dygraphs, highcharter, and plotly, based on the htmlwidgets framework, for interactive graphics.

Materials from previous sessions

2020 - 2021