Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
eval = identical(tolower(Sys.getenv("NOT_CRAN")), "true"),
out.width = "100%"
)
## ----message = FALSE, eval = FALSE--------------------------------------------
# # CRAN
# install.packages("aopdata")
#
# # dev version from github
# utils::remove.packages('aopdata')
# devtools::install_github("ipeaGIT/aopdata", subdir = "r-package")
#
## ----message = FALSE, eval = TRUE---------------------------------------------
library(aopdata)
## ----message = FALSE, eval = TRUE---------------------------------------------
# for English
aopdata_dictionary(lang = 'en')
# for Portuguese
aopdata_dictionary(lang = 'pt')
## ----message = FALSE, eval = TRUE---------------------------------------------
# Download accessibility, population and land use data
cur <- read_access(
city = 'Curitiba',
mode = 'public_transport',
peak = TRUE,
year = 2019,
showProgress = FALSE
)
## ----message = FALSE, eval = TRUE---------------------------------------------
# Download accessibility, population and land use data
cur <- read_access(
city = 'Curitiba',
mode = 'public_transport',
peak = TRUE,
year = 2019,
geometry = TRUE
)
## ----message = FALSE, eval = TRUE---------------------------------------------
# Land use data
lnu_for <- read_landuse(
city = 'Fortaleza',
year = 2019,
geometry = TRUE,
showProgress = FALSE
)
# Population data
pop_for <- read_population(
city = 'Fortaleza',
year = 2010,
geometry = TRUE,
showProgress = FALSE
)
## ----message = FALSE, eval = TRUE---------------------------------------------
h3_for <- read_grid(city = 'Fortaleza', showProgress = FALSE)
head(h3_for)
## ----message = FALSE, eval = TRUE---------------------------------------------
df <- read_access(
city = 'cur',
mode = 'public_transport',
year = 2019,
peak = TRUE,
showProgress = FALSE
)
df <- read_grid(city = 'for', showProgress = FALSE)
## ----message = FALSE, eval = FALSE--------------------------------------------
# all <- read_landuse(city = 'all', year = 2019)
#
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