From 3ff99bb9a0904c2a85a890fb6e6e694dcf59caf8 Mon Sep 17 00:00:00 2001 From: arthur-mac Date: Sun, 22 Oct 2023 12:36:48 -0300 Subject: [PATCH] updated readme --- .DS_Store | Bin 6148 -> 6148 bytes .Rbuildignore | 1 + .github/.gitignore | 1 + .github/workflows/R-CMD-check.yaml | 49 ++++++++++++++++++ R/coef_rqs.R | 6 +-- R/dist_nearest.R | 42 ++++++++++------ R/geom_sf_rais.R | 66 +++++++++++++++++++++++-- R/get_osm.R | 64 +++++++++++++++++------- R/get_rais.R | 4 ++ R/rais_fortaleza.R | 19 +++---- README.md | 25 ++++++++-- data/fortaleza.rda | Bin 277950 -> 278043 bytes data/rais_fortaleza.rda | Bin 67779 -> 4537 bytes man/coef_rqs.Rd | 77 ++--------------------------- man/dist_nearest.Rd | 14 ++++-- man/geom_sf_rais.Rd | 16 ++++-- man/get_osm_.Rd | 58 ++++++++++++++++++++++ man/get_osm_rail.Rd | 24 --------- man/get_osm_roads.Rd | 22 --------- man/get_osm_zips.Rd | 21 -------- man/get_rais.Rd | 4 ++ man/rais_fortaleza.Rd | 21 ++++---- 22 files changed, 325 insertions(+), 209 deletions(-) create mode 100644 .github/.gitignore create mode 100644 .github/workflows/R-CMD-check.yaml create mode 100644 man/get_osm_.Rd delete mode 100644 man/get_osm_rail.Rd delete mode 100644 man/get_osm_roads.Rd delete mode 100644 man/get_osm_zips.Rd diff --git a/.DS_Store b/.DS_Store index eb3149283192bb6b8290d85d75eb94c7b5fc8dd4..351c098ff07dc02efd1ea57db7220f5505e40f70 100644 GIT binary patch delta 39 vcmZoMXffCz$jZ2N@-NmxX3^^E$@y#wjO~*ru*oxaY(Bwi&$OA1;~zf&3GodE delta 21 dcmZoMXffCz$U6B4>#ohGSZ$a#vvd6A2LM}W2nPTF diff --git a/.Rbuildignore b/.Rbuildignore index 4a3189e..5e5cc50 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -2,3 +2,4 @@ ^\.Rproj\.user$ ^data-raw$ ^LICENSE\.md$ +^\.github$ diff --git a/.github/.gitignore b/.github/.gitignore new file mode 100644 index 0000000..2d19fc7 --- /dev/null +++ b/.github/.gitignore @@ -0,0 +1 @@ +*.html diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml new file mode 100644 index 0000000..a3ac618 --- /dev/null +++ b/.github/workflows/R-CMD-check.yaml @@ -0,0 +1,49 @@ +# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples +# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help +on: + push: + branches: [main, master] + pull_request: + branches: [main, master] + +name: R-CMD-check + +jobs: + R-CMD-check: + runs-on: ${{ matrix.config.os }} + + name: ${{ matrix.config.os }} (${{ matrix.config.r }}) + + strategy: + fail-fast: false + matrix: + config: + - {os: macos-latest, r: 'release'} + - {os: windows-latest, r: 'release'} + - {os: ubuntu-latest, r: 'devel', http-user-agent: 'release'} + - {os: ubuntu-latest, r: 'release'} + - {os: ubuntu-latest, r: 'oldrel-1'} + + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + R_KEEP_PKG_SOURCE: yes + + steps: + - uses: actions/checkout@v3 + + - uses: r-lib/actions/setup-pandoc@v2 + + - uses: r-lib/actions/setup-r@v2 + with: + r-version: ${{ matrix.config.r }} + http-user-agent: ${{ matrix.config.http-user-agent }} + use-public-rspm: true + + - uses: r-lib/actions/setup-r-dependencies@v2 + with: + extra-packages: any::rcmdcheck + needs: check + + - uses: r-lib/actions/check-r-package@v2 + with: + upload-snapshots: true diff --git a/R/coef_rqs.R b/R/coef_rqs.R index 38475ca..041e746 100644 --- a/R/coef_rqs.R +++ b/R/coef_rqs.R @@ -6,7 +6,7 @@ #' This makes it easy to make plots with confidence intervals for each coefficient. #' #' @param rqs A `rq` or `rqs` object from `{quantreg}`. -#' @inheritDotParams quantreg::summary.rq +#' @param ... Arguments passed on to [quantreg::summary.rq()] #' #' @import quantreg #' @importFrom dplyr mutate bind_rows @@ -17,6 +17,7 @@ #' #' @returns A `tibble` #' +#' @seealso [quantreg::rq()] coef_rqs <- function(rqs, ...) { summary <- summary(rqs, ...) @@ -26,9 +27,8 @@ coef_rqs <- function(rqs, ...) { \(x) x$coefficients %>% t() %>% - as_tibble() %>% + as_tibble(rownames = "value") %>% mutate( - value = c("coef", "lower_bound", "upper_bound"), quant = x$tau ) ) %>% diff --git a/R/dist_nearest.R b/R/dist_nearest.R index 8cf418f..234053b 100644 --- a/R/dist_nearest.R +++ b/R/dist_nearest.R @@ -1,20 +1,33 @@ #' Distance to the nearest feature +#' +#' @description +#' For each spatial object in x, calculate the distance to the nearest feature in y. +#' #' @param x A `sf` object to calculate distances from. #' @param y A `sf` object to retrieve the closest one to each observation in `x` -#' @param name description An optional argument to set the new column's name, otherwise it is set to "distance". -#' @param id_feature Specifies if an additional column with `y`'s row id should be inserted. Defaults to FALSE. +#' @param name An optional argument to set the new column's name, otherwise it is set to "distance". +#' @param id_feature Specifies if an additional column with `y`'s row id should be inserted. Defaults to `FALSE.` #' @param geometry Specifies the name of the geometry column, if different from the default, to reorder variables. +#' @param drop_units Should units be included? Default: `FALSE` +#' #' @importFrom sf st_nearest_feature st_as_sf st_transform st_crs #' @importFrom tibble tibble rowid_to_column #' @importFrom dplyr left_join mutate bind_cols #' @importFrom units drop_units +#' #' @export -#' @returns Original `x` with an additional column containing the distance to the closest `y` feature. +#' #' @details -#' For each spatial object in x, calculate the distance to the nearest feature in y. +#' `dist_nearest` First finds the closest feature in `y` to each feature in `x`, calculating then +#' pairwise distances faster than e.g. using a for loop and then minimizing distances or +#' calculating distance matrices. +#' +#' @returns Original `x` with an additional column containing the distance to the closest `y` feature. +#' #' @example inst/examples/dist_nearest.R -dist_nearest <- function(x, y, name, id_feature = F, geometry = geometry) { +dist_nearest <- function(x, y, name, id_feature = F, geometry = geometry, drop_units = T) { + closest <- st_nearest_feature(x, y) %>% tibble(id_closest = `.`) @@ -25,20 +38,19 @@ dist_nearest <- function(x, y, name, id_feature = F, geometry = geometry) { if(missing(name)) { x <- x %>% - mutate(distance = st_distance(distance, ., by_element = TRUE), .before = geometry) %>% - drop_units() + mutate(distance = st_distance(distance, ., by_element = TRUE), .before = geometry) } else { x <- x %>% - mutate({{name}} := st_distance(distance, ., by_element = TRUE), .before = geometry) %>% - drop_units() + mutate({{name}} := st_distance(distance, ., by_element = TRUE), .before = geometry) } - if(id_feature == F) { - return(x) - } else { - x <- x %>% - bind_cols(closest) + if(drop_units) { + x <- x %>% drop_units() + } - return(x) + if(id_feature) { + x <- x %>% bind_cols(closest) } + + return(x) } diff --git a/R/geom_sf_rais.R b/R/geom_sf_rais.R index 85f8623..316f2f6 100644 --- a/R/geom_sf_rais.R +++ b/R/geom_sf_rais.R @@ -1,11 +1,18 @@ -#' RAIS thematic maps using ggplot -#' @param x A `data.frame` to plot or an object convertible to it. +#' RAIS maps using ggplot +#' +#' @description +#' An easy way to make maps with data from the Brazilian employer-employee dataset. This function +#' requires an already spatialized dataset +#' +#' @param x Plot variable. #' @param scale_theme Palette theme to be used in the plots, currently "distiller" and "viridis" are supported #' @param palette Optional palette specification. For absolute values, defaults to "YlGnBu" when #' `scale_theme` = "distiller" or "D" if `scale_theme` = "viridis". For relative values, defaults to "RdBu". #' @param direction Palette's direction, defaults to 1. #' @param data_format Specify if data is in absolute (default) or relative format. #' @param data_level Specify if data represents a point value or growth between two periods. +#' @param data An object with classes `sf` and `data.frame` (or convertible to it, see +#' [ggplot2::fortify()]). Optional; will inherit data from previous layers if provided. #' @param auto.labels When `TRUE`, automatically generates title, subtitle, and caption based on `geo_name`, #' `geo_level`, and `var_name`. If `FALSE`, specify `title`, `subtitle`, and `caption`. #' @param geo_name Name of the geographic area being represented. @@ -17,9 +24,58 @@ #' @param faceted Defaults to `FALSE`, change to `TRUE` to use a faceted plot. #' @param facet_var A variable to be passed into `ggplot2::vars()` when faceting. #' @param faceted_labs Labels for the faceted subplots. +#' #' @import ggplot2 +#' #' @export +#' #' @returns A `ggplot` object +#' +#' @examples +#' \dontrun{ +#' # 1 one year +#' +#' data("fortaleza") +#' data("rais_fortaleza") +#' +#' ## get geometry data into dataframe +#' rais_fortaleza <- rais_fortaleza %>% +#' left_join(fortaleza) %>% +#' sf::st_as_sf() %>% +#' filter(year == 2019) +#' +#' ## 1.1 inheriting data from ggplot() +#' rais_fortaleza %>% +#' ggplot() + +#' geom_sf_rais(n_jobs, var_name = "Jobs", geo_name = "Fortaleza", geo_level = "neighborhood") + +#' theme_void() +#' +#' ## 1.2 passing data explicitly +#' ggplot() + +#' geom_sf_rais(n_jobs, var_name = "Jobs", geo_name = "Fortaleza", geo_level = "neighborhood", +#' data = rais_fortaleza) + +#' theme_void() +#' } +#' +#' \dontrun{ +#' # 2 two years (faceted) +#' +#' data("fortaleza") +#' data("rais_fortaleza") +#' +#' ## get geometry data into dataframe +#' rais_fortaleza <- rais_fortaleza %>% +#' left_join(fortaleza) %>% +#' sf::st_as_sf() +#' +#' ## plot +#' ggplot() + +#' geom_sf(data = fortaleza, color = NA) + +#' geom_sf_rais(n_jobs, var_name = "Jobs", geo_name = "Fortaleza", geo_level = "neighborhood", +#' data = rais_fortaleza, +#' faceted = T, facet_var = year) + +#' theme_void() +#' } geom_sf_rais <- function( x, @@ -28,6 +84,7 @@ geom_sf_rais <- function( direction = 1, data_format = c("absolute", "relative"), data_level = c("level", "growth"), + data = NULL, auto.labels = TRUE, geo_name = NULL, geo_level = NULL, var_name = NULL, title = NULL, subtitle = NULL, caption = NULL, @@ -45,12 +102,13 @@ geom_sf_rais <- function( list( title = paste0(var_name, " in ", geo_name), subtitle = paste0(ifelse(data_format == "absolute", "Total", "Growth rate"), - ifelse(is.null(geo_level), NULL, paste0(" per ", geo_level))), + ifelse(is.null(geo_level), "", paste0(" per ", geo_level))), caption = "Note: excludes public administration.\nSource: RAIS/MTE (2023)" ) } else {list(title = title, subtitle = subtitle, caption = caption)} - p <- list(geom_sf(aes(fill = {{x}}, color = {{x}}))) + p <- ifelse(is.null(data), list(geom_sf(aes(fill = {{x}}, color = {{x}}))), + list(geom_sf(data = data, aes(fill = {{x}}, color = {{x}})))) if (data_level == "level") { scale_fill <- scale_fill_distiller diff --git a/R/get_osm.R b/R/get_osm.R index cdb4371..7ef6d59 100644 --- a/R/get_osm.R +++ b/R/get_osm.R @@ -1,14 +1,34 @@ -#' Download osm roads +#' Download osm data +#' #' @description -#' A convenient wrapper for osm features to get roads easily convertible to `sf` format. +#' A convenient wrapper for osm features to get some features I need easily convertible to `sf` format. +#' #' @param bbox A bounding box for the search area. +#' #' @import osmdata -#' @export +#' #' @returns A `list` for each kind of geometry retrieved by osmdata. +#' +#' @seealso [osmdata::add_osm_feature()] + + + +#' @rdname get_osm_ +#' @name get_osm_roads +#' @export +#' #' @details #' Returns values that meet `key` = "highway" and `value` = "motorway", "primary", "secondary", #' "tertiary", "residential", "living_street" and "pedestrian". For more info, please check #' ["Key:highway"](https://wiki.openstreetmap.org/wiki/Key:highway) page at OSM Wiki. +#' +#' @examples +#' \dontrun{ +#' # Get roads in Brazil's smallest city +#' geobr::read_municipality(code_muni = 3157336) %>% +#' sf::st_bbox() %>% +#' get_osm_roads() +#' } get_osm_roads <- function(bbox) { query <- opq(bbox, timeout = 50) %>% @@ -22,16 +42,22 @@ get_osm_roads <- function(bbox) { -#' Download osm postcodes -#' @description -#' A convenient wrapper for osm features to get postcodes easily convertible to `sf` format -#' @param bbox A bounding box for the search area. -#' @import osmdata +#' @rdname get_osm_ +#' @name get_osm_zips #' @export -#' @returns A `list` for each kind of geometry retrieved by osmdata. +#' #' @details #' Returns values that meet `key` = "addr:postcode". For more info, please check #' ["Key:railway"](https://wiki.openstreetmap.org/wiki/Key:railway) page at OSM Wiki. +#' +#' @examples +#' \dontrun{ +#' # Get postcodes in Brazil's smallest city +#' geobr::read_municipality(code_muni = 3157336) %>% +#' sf::st_bbox() %>% +#' get_osm_zips() +#' } + get_osm_zips <- function(bbox) { query <- opq(bbox, timeout = 50) %>% @@ -45,19 +71,23 @@ get_osm_zips <- function(bbox) { -#' Download osm rail transit -#' @description -#' A convenient wrapper for osm features to get (rail) transit lines and stations -#' easily convertible to `sf` format -#' @param bbox A bounding box for the search area. -#' @import osmdata +#' @rdname get_osm_ +#' @name get_osm_rail #' @export -#' @returns Object with classes `list`, `osmdata`, and `osmdata_sf` -#' for each kind of geometry retrieved by osmdata. +#' #' @details #' Returns values that meet `key` = "railway" and `value` = "rail", "light_rail", "subway", "tram", #' "service", "construction", "usage", "station", and "tram_stop". For more info, please check #' ["Key:addr:*"](https://wiki.openstreetmap.org/wiki/Key:addr:*) page at OSM Wiki +#' +#' @examples +#' \dontrun{ +#' # Get railways in Brazil's smallest city +#' geobr::read_municipality(code_muni = 3157336) %>% +#' sf::st_bbox() %>% +#' get_osm_rail() +#' } + get_osm_rail <- function(bbox) { query <- opq(bbox, timeout = 50) %>% diff --git a/R/get_rais.R b/R/get_rais.R index 25b0c5f..76ab7bd 100644 --- a/R/get_rais.R +++ b/R/get_rais.R @@ -19,10 +19,14 @@ #' https://basedosdados.org/dataset/3e7c4d58-96ba-448e-b053-d385a829ef00?table=c3a5121e-f00d-41ff-b46f-bd26be8d4af3. #' @examples #' \dontrun{ +#' # Getting RAIS data for Caete (MG) +#' +#' ## setting variables #' variables <- "ano, quantidade_vinculos_ativos, cnae_2, indicador_atividade_ano" #' source <- "`basedosdados.br_me_rais.microdados_estabelecimentos`" #' city <- "id_municipio='3110004'" #' +#' ## download #' get_rais( #' variables = variables, #' source = source, diff --git a/R/rais_fortaleza.R b/R/rais_fortaleza.R index 1f02d79..87d7ffd 100644 --- a/R/rais_fortaleza.R +++ b/R/rais_fortaleza.R @@ -1,19 +1,20 @@ #' RAIS Firms Data - Fortaleza, 2019 #' -#' A subset of the Brazilian employer-employee dataset (RAIS) for Fortaleza in 2019. Data obtained -#' via package `{basedosdados}`. +#' A subset of the Brazilian employer-employee dataset (RAIS) for Fortaleza in 2019, grouped by +#' neighborhood. Data obtained via package `{basedosdados}`. #' #' @format ## `fortaleza_rais` -#' A tibble with 28,453 rows and 3 columns: +#' A `data.frame` with 65 rows and 6 columns: #' \describe{ -#' \item{ano}{Year (double)} -#' \item{quantidade_vinculos_ativos}{Number of employees per firm (double)} -#' \item{cep}{Firm postcode (double)} -#' \item{cod_bairro_rais}{Neighborhood code in the RAIS dataset (character)} -#' \item{nome_bairro}{Neighborhood name, withouth capital letters os special characters} -#' \item{cod_bairro}{Neighborhood code according to city counsil data (character)} +#' \item{year}{Year (double)} +#' \item{name_neigh}{Neighborhood name, withouth capital letters os special characters} +#' \item{code_neigh}{Neighborhood code according to city counsil data (character)} +#' \item{n_jobd}{Number of employees in the neighborhood (integer)} +#' \item{avg_wage}{Average wage in the neighborhood (double)} +#' \item{avg_wage_h}{Average hourly wage in the neighborhood (diouble)} #' } #' +#' @seealso [basedosdados::download()], [basedosdados::read_sql()] #' @source "rais_fortaleza" diff --git a/README.md b/README.md index df17fc9..bd9ad7e 100644 --- a/README.md +++ b/README.md @@ -2,13 +2,23 @@ # spatialops +[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental) +[![R-CMD-check](https://github.com/baarthur/spatialops/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/baarthur/spatialops/actions/workflows/R-CMD-check.yaml) -The goal of spatialops is to ... +## Spatialops: spatial operations that come in handy + +Built mainly upon the `{sf}` and `{tidyverse}` frameworks, the functions in this package range from simple reading/tidying wrappers to specific spatial operations and random utilities I have used along my journey. Some use cases: + +* read shapefiles directly from a `.zip` whithout creating a mess in your folders with `shp_extract_read` +* calculate the distance between the closest `y` feature from an `x` set of features with `dist_nearest` +* need to manually tidy your shapefiles (e.g. nudge a geometry)? No problem, load them into [MapHub](https://maphub.net/) and then convert the description into useful columns using `maphub_to_sf` +* `gg`plot quantile regression coefficients with `coef_rqs` + ## Installation -You can install the development version of spatialops like so: +You can install the development version of spatialops with `remotes`: ``` r remotes::install_github("https://github.com/baarthur/spatialops") @@ -16,10 +26,17 @@ remotes::install_github("https://github.com/baarthur/spatialops") ## Example -This is a basic example which shows you how to solve a common problem: +Find the distance to the closest subway station in each neighborhood in Fortaleza (Brazil). Very useful in hedonic models and other (spatial) econometric analysis. ``` r library(spatialops) -## basic example code +data("fortaleza") +data("metrofor") + +# select only stations +metrofor <- dplyr::filter(metrofor, railway == "station") + +fortaleza <- fortaleza %>% + dist_nearest(metrofor, name = dist_metro) ``` diff --git a/data/fortaleza.rda b/data/fortaleza.rda index 5990c188fef9700f61ef4c38f015e60ef4007ad8..9a103ef8e7826d730b85f179a8026682cf21cda9 100644 GIT binary patch delta 273473 zcmX`S1z1$y^EiwsNC?s>h}06hl(d3$F3qw_mmsw?5=yP4bnFrW(o5{pNT(v*wREU} zG)OnRe!jo|^Um|!ITQEJ%$YOiJmjB5&Vd1L!mf^tTjdPYl6BX<+Y`DyX+ z@N)3($>QO0_S;U(bV5&To?{O<<*e}aGTuOZOU(ZNF_|HuC4439)dCs&q$TZw}PDN8_b zPd-@|k0cmh{^LIlmHa>bzi|FJ27P=Wi>IrKcTW}Y&uk7}!9Te?MxF%^kLE#eG2T52 z8Uj2LU0GrP9v)1T0RJO5Hx*vNf4-AoN)*K;dBO4@b#&Q2M&&>N+}t2+9+U;E0|rnM zfj<80E&fLUQubfu0$>6HZX(%#PyH`^Dm=Wr$p7g77d;-n?Eez;Px3D}{|P}K@e2ME z{vRm*U!(e;?w>UX$_-!P-zA6m=Yjwa@BRqu**s5kd6#G7*SeJgg>thD<&JNi;d@&z 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zqTO+pN~wZ^)j~en6{XCVbfIje^C??NZiQGx9wAeKG?cI^;uSrVPWH@IYgLevlW2`J zgxV02OGb*qnj|rR$ZTRP1(K8eZEMSF_0Xv05_2MG6Ym8$p-!qK;Ud%vQceP`Qktqm zl%Ze>PLwXyM^o6Ss>IAXMNFeI9->)FPW3M(D`hX5q5D9O2$m@GDr8k3Y?VBcKFKGx zOUe~;6~Qk^RQAHA!Chz01JaaLn3Ld&ebQIrDK}F0s4EnM!B@dbdkR*{ngqR~ zPyS+pvP`D4>43=2084=P#sBrvAOH%~zyJY%&;KBR0Du4h5C8*!17}g11d^E()jgo5 z)b&498KeMc+G;%-fg*uZ^(Ja\% +sf::st_bbox() \%>\% +get_osm_roads() +} +\dontrun{ +# Get postcodes in Brazil's smallest city +geobr::read_municipality(code_muni = 3157336) \%>\% +sf::st_bbox() \%>\% +get_osm_zips() +} +\dontrun{ +# Get railways in Brazil's smallest city +geobr::read_municipality(code_muni = 3157336) \%>\% +sf::st_bbox() \%>\% +get_osm_rail() +} +} +\seealso{ +\code{\link[osmdata:add_osm_feature]{osmdata::add_osm_feature()}} +} diff --git a/man/get_osm_rail.Rd b/man/get_osm_rail.Rd deleted file mode 100644 index 44f8c5f..0000000 --- a/man/get_osm_rail.Rd +++ /dev/null @@ -1,24 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_osm.R -\name{get_osm_rail} -\alias{get_osm_rail} -\title{Download osm rail transit} -\usage{ -get_osm_rail(bbox) -} -\arguments{ -\item{bbox}{A bounding box for the search area.} -} -\value{ -Object with classes \code{list}, \code{osmdata}, and \code{osmdata_sf} -for each kind of geometry retrieved by osmdata. -} -\description{ -A convenient wrapper for osm features to get (rail) transit lines and stations -easily convertible to \code{sf} format -} -\details{ -Returns values that meet \code{key} = "railway" and \code{value} = "rail", "light_rail", "subway", "tram", -"service", "construction", "usage", "station", and "tram_stop". For more info, please check -\href{https://wiki.openstreetmap.org/wiki/Key:addr:*}{"Key:addr:*"} page at OSM Wiki -} diff --git a/man/get_osm_roads.Rd b/man/get_osm_roads.Rd deleted file mode 100644 index f1b561f..0000000 --- a/man/get_osm_roads.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_osm.R -\name{get_osm_roads} -\alias{get_osm_roads} -\title{Download osm roads} -\usage{ -get_osm_roads(bbox) -} -\arguments{ -\item{bbox}{A bounding box for the search area.} -} -\value{ -A \code{list} for each kind of geometry retrieved by osmdata. -} -\description{ -A convenient wrapper for osm features to get roads easily convertible to \code{sf} format. -} -\details{ -Returns values that meet \code{key} = "highway" and \code{value} = "motorway", "primary", "secondary", -"tertiary", "residential", "living_street" and "pedestrian". For more info, please check -\href{https://wiki.openstreetmap.org/wiki/Key:highway}{"Key:highway"} page at OSM Wiki. -} diff --git a/man/get_osm_zips.Rd b/man/get_osm_zips.Rd deleted file mode 100644 index 15ac374..0000000 --- a/man/get_osm_zips.Rd +++ /dev/null @@ -1,21 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_osm.R -\name{get_osm_zips} -\alias{get_osm_zips} -\title{Download osm postcodes} -\usage{ -get_osm_zips(bbox) -} -\arguments{ -\item{bbox}{A bounding box for the search area.} -} -\value{ -A \code{list} for each kind of geometry retrieved by osmdata. -} -\description{ -A convenient wrapper for osm features to get postcodes easily convertible to \code{sf} format -} -\details{ -Returns values that meet \code{key} = "addr:postcode". For more info, please check -\href{https://wiki.openstreetmap.org/wiki/Key:railway}{"Key:railway"} page at OSM Wiki. -} diff --git a/man/get_rais.Rd b/man/get_rais.Rd index a5fa2cd..e1b1bf6 100644 --- a/man/get_rais.Rd +++ b/man/get_rais.Rd @@ -35,10 +35,14 @@ https://basedosdados.org/dataset/3e7c4d58-96ba-448e-b053-d385a829ef00?table=c3a5 } \examples{ \dontrun{ +# Getting RAIS data for Caete (MG) + +## setting variables variables <- "ano, quantidade_vinculos_ativos, cnae_2, indicador_atividade_ano" source <- "`basedosdados.br_me_rais.microdados_estabelecimentos`" city <- "id_municipio='3110004'" +## download get_rais( variables = variables, source = source, diff --git a/man/rais_fortaleza.Rd b/man/rais_fortaleza.Rd index 9121363..a62c879 100644 --- a/man/rais_fortaleza.Rd +++ b/man/rais_fortaleza.Rd @@ -7,14 +7,14 @@ \format{ \subsection{\code{fortaleza_rais}}{ -A tibble with 28,453 rows and 3 columns: +A \code{data.frame} with 65 rows and 6 columns: \describe{ -\item{ano}{Year (double)} -\item{quantidade_vinculos_ativos}{Number of employees per firm (double)} -\item{cep}{Firm postcode (double)} -\item{cod_bairro_rais}{Neighborhood code in the RAIS dataset (character)} -\item{nome_bairro}{Neighborhood name, withouth capital letters os special characters} -\item{cod_bairro}{Neighborhood code according to city counsil data (character)} +\item{year}{Year (double)} +\item{name_neigh}{Neighborhood name, withouth capital letters os special characters} +\item{code_neigh}{Neighborhood code according to city counsil data (character)} +\item{n_jobd}{Number of employees in the neighborhood (integer)} +\item{avg_wage}{Average wage in the neighborhood (double)} +\item{avg_wage_h}{Average hourly wage in the neighborhood (diouble)} } } } @@ -25,7 +25,10 @@ A tibble with 28,453 rows and 3 columns: rais_fortaleza } \description{ -A subset of the Brazilian employer-employee dataset (RAIS) for Fortaleza in 2019. Data obtained -via package \code{{basedosdados}}. +A subset of the Brazilian employer-employee dataset (RAIS) for Fortaleza in 2019, grouped by +neighborhood. Data obtained via package \code{{basedosdados}}. +} +\seealso{ +\code{\link[basedosdados:download]{basedosdados::download()}}, \code{\link[basedosdados:read_sql]{basedosdados::read_sql()}} } \keyword{datasets}