BlasBenito

#impute NA with group mean
df <- df %>%
  group_by(
    grouping_column_1,
    grouping_column_2
    ) %>%
  mutate_at(
      all_of(target_columns),
      ~ ifelse(is.na(.), mean(., na.rm = TRUE), .)
  )

BlasBenito

#!/bin/bash	
#reprojects in parallel geotif files in MODIS sinusoidal 
#in the "raw" folder
#to geotif files in EPSG 4326 in the current folder
#with the suffix "_wgs_84"

#listing files in raw
for FILEPATH in raw/*; do

  #generates output file name

BlasBenito

#!/bin/bash	
#reprojects a geotif from MODIS sinusoidal to EPSG 4326
#check https://gdal.org/programs/gdalwarp.html for further details
gdalwarp \
  -of GTIFF \
  -multi \
  --config GDAL_CACHEMAX 1024 \
  -s_srs '+proj=sinu +R=6371007.181 +nadgrids=@null +wktext' \
  -t_srs '+proj=longlat +datum=WGS84 +no_defs' \
  -r near \

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# import config.
# You can change the default config with `make cnf="config_special.env" build`
cnf ?= config.env
include $(cnf)
export $(shell sed 's/=.*//' $(cnf))

# import deploy config
# You can change the default deploy config with `make cnf="deploy_special.env" release`
dpl ?= deploy.env
include $(dpl)

BlasBenito

#R script to plot the CRAN download history of a set of packages

library(dlstats)
library(ggplot2)

target.packages <- c("ranger", "randomForest", "xgboost")

x <- dlstats::cran_stats(packages = target.packages)

ggplot2::ggplot(data = x) + 

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#This script downloads soilgrids (https://www.isric.org/explore/soilgrids) data 
#at a given resolution (variable "res", in degrees) and the depth intervals 0-5 and 5-15
#to compute the mean for the depth interval 0-15.
#It also applies the conversion factor shown in the FAQ (https://www.isric.org/explore/soilgrids/faq-soilgrids#How_can_I_access_SoilGrids)
#to reconstitute the original data units.

library(gdalUtils)
library(raster)

#variables to download

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#installing the development version of the package (v.1.1.1)
remotes::install_github(
  repo = "blasbenito/spatialRF", 
  ref = "development",
  force = TRUE,
  quiet = TRUE
  )
library(spatialRF)

#loading the example data

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#installing and loading package
remotes::install_github(
  repo = "blasbenito/spatialRF", 
  ref = "main",
  force = TRUE,
  quiet = TRUE
)
library(spatialRF)
library(magrittr)

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#preparing data
library(car)
data("Prestige")
df <- Prestige[, c(
  "income",
  "education",
  "prestige"
)]

#making a version of education with its range crossing 0

BlasBenito

#returns biodiversity components a, b, and c from two vectors with taxa names.
#x: character vector, taxa list of one site
#y: character vector, taxa list of another site
abc <- function(x, y){
  
  #list to store output
  out <- list()
  
  #filling the list
  out$a <- length(intersect(x, y))