## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup, warning=FALSE, message=FALSE-------------------------------------- library(findSVI) library(dplyr) ## ----get_census_data, eval=FALSE---------------------------------------------- # data <- get_census_data(2018, "zcta", "RI") # data[1:10, 1:10] ## ----RI_2018raw, echo=FALSE--------------------------------------------------- load(system.file("extdata", "ri_zcta_raw2018.rda", package = "findSVI")) ri_zcta_raw2018[1:10, 1:10] ## ----get_svi, eval=FALSE------------------------------------------------------ # result <- get_svi(2018, data) # glimpse(result) ## ----RI_result2018, echo=FALSE------------------------------------------------ load(system.file("extdata", "ri_zcta_svi2018.rda", package = "findSVI")) glimpse(ri_zcta_svi2018) ## ----find_svi, eval=FALSE----------------------------------------------------- # onestep_result <- find_svi(2018, "RI", "zcta") # onestep_result %>% head(10) ## ----RI_result_RPL, echo=FALSE------------------------------------------------ ri_zcta_svi2018 %>% select(GEOID, contains("RPL_theme")) %>% mutate(year = 2018, state = "RI") %>% head(10) ## ----find_svi_vector, eval=FALSE---------------------------------------------- # summarise_results <- find_svi( # year = c(2017, 2018), # state = c("NJ", "PA"), # geography = "county" # ) # # summarise_results %>% # group_by(year, state) %>% # slice_head(n = 5) ## ----summarise_results_RPL, echo=FALSE---------------------------------------- load(system.file("extdata", "summarise_results.rda", package = "findSVI")) summarise_results %>% group_by(year, state) %>% slice_head(n = 5) ## ----info_table, echo=FALSE--------------------------------------------------- year <- c(2017,2018, 2014, 2018, 2013, 2020) state <- c("AZ", "FL", "FL", "PA", "MA", "KY") info_table <- data.frame(year, state) info_table ## ----column_find_svi, eval=FALSE---------------------------------------------- # all_results <- find_svi( # year = info_table$year, # state = info_table$state, # geography = "county" # ) # # all_results %>% # group_by(year, state) %>% # slice_head(n = 3) ## ----echo=FALSE--------------------------------------------------------------- load(system.file("extdata", "slice_all_results.rda", package = "findSVI")) slice_all_results ## ----eval=FALSE--------------------------------------------------------------- # cz_svi2020 <- find_svi_x( # year = 2020, # geography = "county", # xwalk = cty_cz_2020_xwalk #county-commuting zone crosswalk # ) # # cz_svi2020 %>% # select(GEOID, contains("RPL")) %>% # head(10) ## ----echo=FALSE--------------------------------------------------------------- load(system.file("extdata","cz_svi2020.rda",package = "findSVI")) cz_svi2020