R

Nicolas

2 minute read

Big dataset (Ok, not so big) df <- tibble::tribble( ~ID, ~city, ~lat, ~lon, 1172, "Zaria", 11.11128, 7.7227, 1173, "Oslo", 59.91273, 10.74609, 1174, "Masqat (Muscat)", 23.61387, 58.5922, 1175, "Bahawalpur", 29.4, 71.68333, 1181,"Islamabad",33.70351,73.059373, 1194,"Rawalpindi",33.6,73.0666667 ) df ## # A tibble: 6 x 4 ## ID city lat lon ## <dbl> <chr> <dbl> <dbl> ## 1 1172 Zaria 11.1 7.72 ## 2 1173 Oslo 59.9 10.7 ## 3 1174 Masqat (Muscat) 23.6 58.6 ## 4 1175 Bahawalpur 29.

Nicolas

8 minute read

This post is based on a notebook I started about R spatial analysis for the project OSGeoLive It aims to provide a quick introduction to R spatial analysis and cartography and will be extended. R is a language dedicated to statistics and data analysis. It has also a lot of strong packages for spatial analysis. Recent packages like {sf} allows easy Simple Features manipulation. This document aims to complete the R Overview and R Quickstart.

Nicolas

2 minute read

Hello, the project that I was talking about earlier is finally over. But it tooks me (and my colleagues) so much time to do that I wasn’t able to post about it. Anyway, the project website is online and can be seen there: http://m2_projet_mexique.frama.io/website/ Ok, it is in French but, first, it is for a French diploma in a French university, so… And second, I’ll make translations of the posts here.