RStats |

Managing R script dependencies: automagic and renv

Thu, 14 Jul 2022 13:00:06 +0000

At the end of the we had an interesting discussion on the need for reproducibility. This talk introduces the concept of reproducibility and focuses on one of it’s many facets: that of managing R script’s dependencies.

In order to do so, two different methods will be presented, compared and discussed: the simple yet works-out-of-the-box {automagic} and the more complex, yet backed up by RStudio, {renv}

At the end of the session, points in common as well as limitations will be highlighted, hopefully leading to a discussion and opening the door for the second talk of the reproducibility series.

Visualisation tool for a grounded FEW Nexus

Fri, 20 May 2022 00:00:00 +0000

Streetscape Perception Modelling – Theoretical Considerations and Methodological Possibilities

Fri, 17 Dec 2021 13:00:06 +0000

The influence of features and properties of the urban built-up environment on people’s sense of safety and perception of beauty, social vibrancy, and walkability is a topic of interest of urban geographers, designers, planners, and environmental psychologists alike. Along with emerging forms of data and the computational paradigm of Artificial Intelligence, current GIS, citizen science, and sensor technologies offer exciting technical and methodological possibilities for extracting, representing, and modelling aspects of people’s perception of streetscapes. This workshop aims to explore these possibilities, exchange research experiences, and discuss the theoretical grounds based on which we can operationalise, i.e., model, streetscape perception, particularly based on geospatial technologies.

The workshop will offer an open and interactive environment for researchers of all levels to discuss questions including, but not limited to:

What theoretical frameworks can guide us in extracting, representing, and modelling different streetscape perception aspects of people from different social groups and cultural backgrounds?
Which variables, parameters, and indicators these theoretical frameworks suggest and how can they be reliably extracted based on different digital technologies and participation methods?
Which GIS interfaces, data structures, and visualisations are effective in representing people’s perception of streetscapes as to foster theory development and inform planning and policy design towards more sustainable and inclusive urban spaces?

An outcome of the workshop will be a written summary of the discussed ideas authored by all participants and published in the PLATIAL’21 proceedings. The indicative programme is as follows:

Introduction by the organisers (20 min)
Crash presentations by participants (optional) (20 min)
Break-out group discussions (30 min) + World Café (30 min)
Paper writing outlook (20 min)

Some R Packages I would love to explore (October 2020)

Tue, 20 Oct 2020 00:00:00 +0000

These are some packages I have just discovered which I would like to try/use in the future. For future reference, I have added a brief description and links to source code:

Data munging:

: has simple functions for examining and cleaning dirty data. It was built with beginning and intermediate R users in mind and is optimized for user-friendliness. Advanced R users can already do everything covered here, but with janitor they can do it faster and save their thinking for the fun stuff.
makes writing regular expressions easier by using a friendlier syntax. I always have some difficulties memorizing regex expressions and usually have to use the (a great resource, by the way) as a reminder.
the + + + team. These group of packages from the same author seem to work as a team. validate validates data’s structure (It can even validate data written in yaml), errorlocate finds the faulty observations, which can later be corrected by either dcmodify or deductive (from predefinded rules)

Visualization:

provides additional Themes and Theme Components for my beloved ggplot2.
provides additional color palettes and backgrounds for ggplot
: positioning annotations in ggplot.

Geospatial:

: a mapzen API client for R ( ). I am always looking for good geocoding services (currently using ), and this package uses Mapzen’s Pelias geocoding (amongst other things).
parses messy coordinates and converts from different formats to decimal. Also, provides helper functions such as getting hemisphere.