osmdata, rnaturalearth and magick for #TidyTuesday

jkaupp · November 6, 2020, 2:47am

rOpenSci package or resource used*

osmdata, rnaturalearth, magick

What did you do?

I used these packages to create my submission for week 44 of #TidyTuesday, Canadian Wind Turbines. TidyTuesday is a weekly social visualization activity/project/challenge originating out of the R4DS and larger R community. rnaturalearth provided me with an excellent map of Maritime Canada, osmdata for the main highways (using simple features too!) and magick for the no-fuss image cropping!

URL or code snippet for your use case*

github.com

jkaupp/tidytuesdays/blob/437b47ad14bd3d6d66dca41e0a4a84c9d96716fb/2020/week44/R/analysis.R

library(tidyverse)
library(osmdata)
library(sf)
library(rnaturalearth)
library(jkmisc)
library(here)
library(colorspace)
library(ggtext)
library(glue)

wind_turbine <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-10-27/wind-turbine.csv')


maritimes_turbines <- filter(wind_turbine, province_territory %in% c("Nova Scotia", "New Brunswick", "Prince Edward Island")) %>% 
  mutate(height_bin = cut(hub_height_m, c(0, 50, 75, 100, Inf), labels = c("0-50m", "51-75m", "76-100m", "100+m"), include.lowest = FALSE))


power <- maritimes_turbines %>% 
  group_by(project_name) %>% 
  summarize(total_project_capacity_mw = unique(total_project_capacity_mw),

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Image

Twitter handle

@jakekaupp

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