## ----echo = FALSE------------------------------------------------------------- # knitr::opts_knit$set(root.dir = paste0(getwd(), '/vignettes')) ## ---- eval = FALSE------------------------------------------------------------ # install.packages("ipeadatar") # library(ipeadatar) ## ---- eval = FALSE------------------------------------------------------------ # library(devtools) # install_github("gomesleduardo/ipeadatar") # library(ipeadatar) ## ----echo = FALSE, message = FALSE, warning = FALSE, eval = FALSE------------- # library(DT) # datatable(available_series(), caption = '', options = list(pageLength = 3)) ## ----echo = TRUE, eval = FALSE------------------------------------------------ # ipeadatar::search_series(terms = 'Taxa de câmbio nominal', fields = c('name')) ## ----echo = FALSE, eval = FALSE----------------------------------------------- # datatable(ipeadatar::search_series(terms = 'Taxa de câmbio nominal', fields = c('name')), caption = '', options = list(pageLength = 3)) ## ----echo = TRUE, eval = FALSE, eval = FALSE---------------------------------- # ipeadatar::search_series(terms = 'Active', fields = c('status')) ## ----echo = FALSE, eval = FALSE----------------------------------------------- # datatable(ipeadatar::search_series(terms = 'Active', fields = c('status')), caption = '', options = list(pageLength = 3)) ## ----echo = TRUE, eval = FALSE------------------------------------------------ # metadata('PRECOS12_IPCA12') ## ----echo = FALSE, eval = TRUE, cache = TRUE, eval = FALSE-------------------- # suppressWarnings(suppressPackageStartupMessages(library(magrittr))) # suppressWarnings(suppressPackageStartupMessages(library(dplyr))) # suppressWarnings(suppressPackageStartupMessages(library(kableExtra))) # # df_m <- # metadata('PRECOS12_IPCA12') %>% # select(code, name, comment, lastupdate, bname, source, sourcename) # # kable(df_m, caption = '') ## ----echo = FALSE, cache = TRUE, fig.align = 'center', fig.width = 7.5, fig.height = 3.75, eval = FALSE---- # ipeadata('PRECOS12_IPCA12') ## ----out.width = '60%', echo = FALSE, cache = TRUE, fig.align = 'center', eval = FALSE---- # df <- ts(ipeadata('PRECOS12_IPCA12')$value, start = c(1979, 12), freq = 12) # # library(dygraphs) # # dygraph(df) %>% # dyOptions(stackedGraph = TRUE) %>% # dyRangeSelector(height = 20) %>% # dySeries("V1", label = "IPCA") %>% # dyOptions(fillGraph = TRUE, fillAlpha = 0.4, colors = "blue") ## ----eval = FALSE, cache = TRUE, eval = FALSE--------------------------------- # homic_rate1995 <- # ipeadata("THOMIC") %>% # filter(uname == "States" & date == "1995-01-01") # # homic_rate2000 <- # ipeadata("THOMIC") %>% # filter(uname == "States" & date == "2000-01-01") # # homic_rate2005 <- # ipeadata("THOMIC") %>% # filter(uname == "States" & date == "2005-01-01") # # homic_rate2010 <- # ipeadata("THOMIC") %>% # filter(uname == "States" & date == "2010-01-01") ## ----message = FALSE, warning = FALSE, include = FALSE, paged.print = FALSE, cache = TRUE, eval = FALSE---- # library(spdep) # library(rgdal) # library(leaflet) # library(RColorBrewer) # library(mapview) # # # Import shapefile (Brazil map - States) ---- # # shp <- readOGR("br_unidades_da_federacao", "BRUFE250GC_SIR", stringsAsFactors = FALSE, encoding = "UTF-8") # # # Import dataset ---- # # homic_rate1995 <- # ipeadata("THOMIC") %>% # filter(uname == "States" & date == "1995-01-01") # # homic_rate2000 <- # ipeadata("THOMIC") %>% # filter(uname == "States" & date == "2000-01-01") # # homic_rate2005 <- # ipeadata("THOMIC") %>% # filter(uname == "States" & date == "2005-01-01") # # homic_rate2010 <- # ipeadata("THOMIC") %>% # filter(uname == "States" & date == "2010-01-01") # # # Import IBGE codes and add to dataset ---- # # ibge <- read.csv2("cod.csv") # homic_rate1995 <- merge(homic_rate1995, ibge, by.x = "tcode", by.y = "Código.UF") # homic_rate2000 <- merge(homic_rate2000, ibge, by.x = "tcode", by.y = "Código.UF") # homic_rate2005 <- merge(homic_rate2005, ibge, by.x = "tcode", by.y = "Código.UF") # homic_rate2010 <- merge(homic_rate2010, ibge, by.x = "tcode", by.y = "Código.UF") # # # Merge dataset and shapefile ---- # # shp_homic_rate1995 <- merge(shp, homic_rate1995, by.x = "CD_GEOCUF", by.y = "tcode") # shp_homic_rate2000 <- merge(shp, homic_rate2000, by.x = "CD_GEOCUF", by.y = "tcode") # shp_homic_rate2005 <- merge(shp, homic_rate2005, by.x = "CD_GEOCUF", by.y = "tcode") # shp_homic_rate2010 <- merge(shp, homic_rate2010, by.x = "CD_GEOCUF", by.y = "tcode") # # shp_homic_rate1995$value <- round(shp_homic_rate1995$value, 2) # shp_homic_rate2000$value <- round(shp_homic_rate2000$value, 2) # shp_homic_rate2005$value <- round(shp_homic_rate2005$value, 2) # shp_homic_rate2010$value <- round(shp_homic_rate2010$value, 2) # # # Transform data ---- # # # add geographical coordinates # proj4string(shp_homic_rate1995) <- CRS("+proj=longlat +datum=WGS84 +no_defs") # proj4string(shp_homic_rate2000) <- CRS("+proj=longlat +datum=WGS84 +no_defs") # proj4string(shp_homic_rate2005) <- CRS("+proj=longlat +datum=WGS84 +no_defs") # proj4string(shp_homic_rate2010) <- CRS("+proj=longlat +datum=WGS84 +no_defs") # # Encoding(shp_homic_rate1995$NM_ESTADO) <- "UTF-8" # Encoding(shp_homic_rate2000$NM_ESTADO) <- "UTF-8" # Encoding(shp_homic_rate2005$NM_ESTADO) <- "UTF-8" # Encoding(shp_homic_rate2010$NM_ESTADO) <- "UTF-8" # # .simpleCap <- function(x) { # s <- strsplit(x, " ")[[1]] # x <- paste(toupper(substring(s, 1, 1)), tolower(substring(s, 2)), # sep = "", collapse = " ") # s <- strsplit(x, " ")[[1]] # s <- ifelse(nchar(s) > 2, s, tolower(s)) # paste(s, sep = "", collapse = " ") # } # # # Edit States names # shp_homic_rate1995$NM_ESTADO <- sapply(shp_homic_rate1995$NM_ESTADO, .simpleCap, USE.NAMES = FALSE) # shp_homic_rate2000$NM_ESTADO <- sapply(shp_homic_rate2000$NM_ESTADO, .simpleCap, USE.NAMES = FALSE) # shp_homic_rate2005$NM_ESTADO <- sapply(shp_homic_rate2005$NM_ESTADO, .simpleCap, USE.NAMES = FALSE) # shp_homic_rate2010$NM_ESTADO <- sapply(shp_homic_rate2010$NM_ESTADO, .simpleCap, USE.NAMES = FALSE) # # # replace NA # shp_homic_rate1995$value[is.na(shp_homic_rate1995$value)] <- 0 # shp_homic_rate2000$value[is.na(shp_homic_rate2000$value)] <- 0 # shp_homic_rate2005$value[is.na(shp_homic_rate2005$value)] <- 0 # shp_homic_rate2010$value[is.na(shp_homic_rate2010$value)] <- 0 ## ----echo = FALSE, fig.width = 8, cache = TRUE, eval = FALSE------------------ # # # Generate map ---- # # pal <- colorBin(brewer.pal(n = 7, name = "Reds"), domain = c(0, 70), n = 7) # Map colors # # state_popup1995 <- paste0("State: ", # paste0(shp_homic_rate1995$NM_ESTADO, " (", shp_homic_rate1995$UF,")"), # "
Homicide rate: ", # shp_homic_rate1995$value) # # state_popup2000 <- paste0("State: ", # paste0(shp_homic_rate2000$NM_ESTADO, " (", shp_homic_rate2000$UF,")"), # "
Homicide rate: ", # shp_homic_rate2000$value) # # state_popup2005 <- paste0("State: ", # paste0(shp_homic_rate2005$NM_ESTADO, " (", shp_homic_rate2005$UF,")"), # "
Homicide rate: ", # shp_homic_rate2005$value) # # state_popup2010 <- paste0("State: ", # paste0(shp_homic_rate2010$NM_ESTADO, " (", shp_homic_rate2010$UF,")"), # "
Homicide rate: ", # shp_homic_rate2010$value) # # graph1995 <- # leaflet(data = shp_homic_rate1995) %>% # addProviderTiles("CartoDB.Positron") %>% # addPolygons(fillColor = ~pal(shp_homic_rate1995$value), # fillOpacity = 0.8, # color = "#BDBDC3", # weight = 1, # popup = state_popup1995) %>% # addLegend("bottomleft", pal = pal, values = ~shp_homic_rate1995$value, # title = "Homicide rate (1995)", # opacity = 1) # # graph2000 <- # leaflet(data = shp_homic_rate2000) %>% # addProviderTiles("CartoDB.Positron") %>% # addPolygons(fillColor = ~pal(shp_homic_rate2000$value), # fillOpacity = 0.8, # color = "#BDBDC3", # weight = 1, # popup = state_popup2000) %>% # addLegend("bottomleft", pal = pal, values = ~shp_homic_rate2000$value, # title = "Homicide rate (2000)", # opacity = 1) # # graph2005 <- # leaflet(data = shp_homic_rate2005) %>% # addProviderTiles("CartoDB.Positron") %>% # addPolygons(fillColor = ~pal(shp_homic_rate2005$value), # fillOpacity = 0.8, # color = "#BDBDC3", # weight = 1, # popup = state_popup2005) %>% # addLegend("bottomleft", pal = pal, values = ~shp_homic_rate2005$value, # title = "Homicide rate (2005)", # opacity = 1) # # graph2010 <- # leaflet(data = shp_homic_rate2010) %>% # addProviderTiles("CartoDB.Positron") %>% # addPolygons(fillColor = ~pal(shp_homic_rate2010$value), # fillOpacity = 0.8, # color = "#BDBDC3", # weight = 1, # popup = state_popup2010) %>% # addLegend("bottomleft", pal = pal, values = ~shp_homic_rate2010$value, # title = "Homicide rate (2010)", # opacity = 1) # # latticeView(graph1995, graph2000, graph2005, graph2010, ncol = 2, sync = "all", sync.cursor = TRUE) ## ----eval = FALSE, cache = TRUE, eval = FALSE--------------------------------- # avg_yschol1991 <- # ipeadata("MEDUCA") %>% # filter(uname == "Mesoregions" & date == "1991-01-01") # # avg_yschol2000 <- # ipeadata("MEDUCA") %>% # filter(uname == "Mesoregions" & date == "2000-01-01") ## ----message = FALSE, warning = FALSE, include = FALSE, paged.print = FALSE, cache = TRUE, eval = FALSE---- # # Import shapefile (Brazil map - Municipalities) ---- # # shp1 <- readOGR("br_mesorregioes", "BRMEE250GC_SIR", stringsAsFactors = FALSE, encoding = "UTF-8") # # # Import dataset ---- # # avg_yschol1991 <- # ipeadata("MEDUCA") %>% # filter(uname == "Mesoregions" & date == "1991-01-01") # # avg_yschol2000 <- # ipeadata("MEDUCA") %>% # filter(uname == "Mesoregions" & date == "2000-01-01") # # # Import IBGE codes and add to dataset ---- # # ibge1 <- read.csv2("cod_meso.csv") # avg_yschol1991 <- merge(avg_yschol1991, ibge1, by.x = "tcode", by.y = "Código.Meso") # avg_yschol2000 <- merge(avg_yschol2000, ibge1, by.x = "tcode", by.y = "Código.Meso") # # # Merge dataset and shapefile ---- # # shp_avg_yschol1991 <- merge(shp1, avg_yschol1991, by.x = "CD_GEOCME", by.y = "tcode") # shp_avg_yschol2000 <- merge(shp1, avg_yschol2000, by.x = "CD_GEOCME", by.y = "tcode") # # shp_avg_yschol1991$value <- round(shp_avg_yschol1991$value, 2) # shp_avg_yschol2000$value <- round(shp_avg_yschol2000$value, 2) # # # Transform data ---- # # # add geographical coordinates # # proj4string(shp_avg_yschol1991) <- CRS("+proj=longlat +datum=WGS84 +no_defs") # proj4string(shp_avg_yschol2000) <- CRS("+proj=longlat +datum=WGS84 +no_defs") # # Encoding(shp_avg_yschol1991$NM_MESO) <- "UTF-8" # Encoding(shp_avg_yschol2000$NM_MESO) <- "UTF-8" # # # Edit Mesoregions names # # .simpleCap <- function(x) { # s <- strsplit(x, " ")[[1]] # x <- paste(toupper(substring(s, 1, 1)), tolower(substring(s, 2)), # sep = "", collapse = " ") # s <- strsplit(x, " ")[[1]] # s <- ifelse(nchar(s) > 2, s, tolower(s)) # paste(s, sep = "", collapse = " ") # } # # shp_avg_yschol1991$NM_MESO <- sapply(shp_avg_yschol1991$NM_MESO, .simpleCap, USE.NAMES = FALSE) # shp_avg_yschol2000$NM_MESO <- sapply(shp_avg_yschol2000$NM_MESO, .simpleCap, USE.NAMES = FALSE) # # # replace NA # # shp_avg_yschol1991$value[is.na(shp_avg_yschol1991$value)] <- 0 # shp_avg_yschol2000$value[is.na(shp_avg_yschol2000$value)] <- 0 ## ----echo = FALSE, fig.width = 8, cache = TRUE, eval = FALSE------------------ # # Generate map ---- # # pal1 <- colorBin(brewer.pal(n = 8, name = "RdYlGn"), domain = c(1, 9), n = 9) # Map colors # # meso_popup1991 <- paste0("Mesoregion: ", # paste0(shp_avg_yschol1991$NM_MESO, " (", shp_avg_yschol1991$UF,")"), # "
Average years: ", # shp_avg_yschol1991$value) # # meso_popup2000 <- paste0("Mesoregion: ", # paste0(shp_avg_yschol1991$NM_MESO, " (", shp_avg_yschol1991$UF,")"), # "
Average years: ", # shp_avg_yschol2000$value) # # graph11991 <- # leaflet(data = shp_avg_yschol1991) %>% # addProviderTiles("CartoDB.Positron") %>% # addPolygons(fillColor = ~pal1(shp_avg_yschol1991$value), # fillOpacity = 0.8, # color = "#BDBDC3", # weight = 1, # popup = meso_popup1991) %>% # addLegend("bottomleft", pal = pal1, values = ~shp_avg_yschol1991$value, # title = "Schooling (1991)", # opacity = 1) # # graph12000 <- # leaflet(data = shp_avg_yschol2000) %>% # addProviderTiles("CartoDB.Positron") %>% # addPolygons(fillColor = ~pal1(shp_avg_yschol2000$value), # fillOpacity = 0.8, # color = "#BDBDC3", # weight = 1, # popup = meso_popup2000) %>% # addLegend("bottomleft", pal = pal1, values = ~shp_avg_yschol2000$value, # title = "Schooling (2000)", # opacity = 1) # # latticeView(graph11991, graph12000, ncol = 2, sync = "all", sync.cursor = TRUE)