Name: Efficient R- programming: Speeding up your R- code
Start: 2018-12-11T18:30:00+01:00
End: 2018-12-11T21:30:00+01:00
Location: Roeterseiland Campus- Building C- Room TBA

Hi Everyone! We are thrilled to announce our next workshop, a workshop on efficient R- programming brought to you by Josephine Daub, a post- doctoral researcher and bioinformatician at the Prinses Maxima Centrum.

---------------------------------------------------------
18:30 Doors open, & welcome

19.00 Introduction to R- Ladies

19.05 Getting into efficient programming part 1

19.45 Break

19.55 Getting into efficient programming part 2

20.45- 21.30 Socialising & look ahead
---------------------------------------------------------

PROGRAMME
R is a popular programming language because of its ease of scripting and visualisation, and because of the availability of a huge number of packages that allow for any kind of statistical analysis. However, the often-heard complaint is that R can be very slow, especially when using for-loops. During this workshop we will first look at ways to find out which part of our script is slow. We next try simple tricks to speed up our R code, and we will discuss how to avoid for-loops (or keep them, but run them in another language). Finally, if time allows, we will find fast solutions to aggregate data as alternative to the slow R function ‘aggregate’.

REQUIREMENTS
In order to most benefit from this workshop, a basic understanding of R is required! Also, please don’t forget your fully charged laptop!

CODE OF CONDUCT
We expect all attendees to abide by our Code of Conduct. Anyone who violates this community's Code of Conduct will be refused entry, expelled, and/or any other action deemed appropriate by the Organizer, regardless of event registration, meetup membership or other condition. We are emphatically queer and trans-friendly. This group was created so those who identify as women have a comfortable place to learn.

ilse pit

ivanovaos

Janine Khuc

Tess Korthout

R-Ladies Amsterdam

R-Ladies

Technology

Open Source

Big Data

Machine Learning

Data Analytics

Data Science

Data Science using R

Data Visualization

Computer Programming

Professional Networking