tests/PDB/tract-variables.R

In jlivsey/Dvar: What the Package Does (One Line, Title Case)

library(jsonlite)
library(dplyr)

# PDB for State data
data_url2 = "https://api.census.gov/data/2020/pdb/statecounty?get=Males_CEN_2010,Females_CEN_2010,Tot_Population_CEN_2010&for=state:*&key=25488af6841e29e4b76b5e8fb877ea0d4ae2a017"

json_data <- fromJSON(data_url2)

pbd_dat <- data.frame(json_data[-1,])
colnames(pbd_dat) <- json_data[1,]

head(pbd_dat)


# ---- All tracts in Virginia ----
# have non-hispanic white alone but do not have hispanic white alone (subtract?)

# "HWA_MALE", "HWA_FEMALE",   --> TOTAL_POP - NH_White_alone_CEN_2010
# "NHWA_MALE", "NHWA_FEMALE", --> NH_White_alone_CEN_2010
# "HBA_MALE", "HBA_FEMALE",   --> TOTAL_POP - NH_Blk_alone_CEN_2010
# "NHBA_MALE", "NHBA_FEMALE", --> NH_Blk_alone_CEN_2010
# "HAA_MALE", "HAA_FEMALE",   --> TOTAL_POP - NH_Asian_alone_CEN_2010
# "NHAA_MALE", "NHAA_FEMALE", --> NH_Asian_alone_CEN_2010
# "HIA_MALE", "HIA_FEMALE",   --> TOTAL_POP - NH_AIAN_alone_CEN_2010
# "NHIA_MALE", "NHIA_FEMALE", --> NH_AIAN_alone_CEN_2010
# "HNA_MALE", "HNA_FEMALE",   --> TOTAL_POP - NH_NHOPI_alone_CEN_2010
# "NHNA_MALE", "NHNA_FEMALE", --> NH_NHOPI_alone_CEN_2010
# "H_MALE"  ,   "H_FEMALE",   --> Hispanic_CEN_2010
# "NH_MALE",   "NH_FEMALE",  --> TOTAL_POP - Hispanic_CEN_2010
# "HTOM_MALE","HTOM_FEMALE",
# "NHTOM_MALE","NHTOM_FEMALE"
#
#
# Additional --> NH_SOR_alone_CEN_2010 ("some other race")

data_url2 = "https://api.census.gov/data/2019/pdb/tract?get=State_name,Tot_Population_ACS_13_17,NH_White_alone_CEN_2010,NH_Blk_alone_CEN_2010,NH_Asian_alone_CEN_2010,NH_NHOPI_alone_CEN_2010,NH_SOR_alone_CEN_2010,Hispanic_CEN_2010,County_name&for=tract:*&in=state:51&in=county:*&key=25488af6841e29e4b76b5e8fb877ea0d4ae2a017"

json_data <- fromJSON(data_url2)

pbd_dat <- data.frame(json_data[-1,])
colnames(pbd_dat) <- json_data[1,]

head(pbd_dat)

# Filter by Counties Eric selected
county_list <- c(
  "Culpeper County",
  "Halifax County",
  "Madison County",
  "Northumberland County",
  "Rockbridge County",
  "Harrisonburg city",
  "Hopewell city"
)

dat <- pbd_dat %>%
  filter(County_name %in% county_list)


#' # ---- Quick look at estimates ----
#' library(tigris)
#' library(sf)
#'
#' dat <- pbd_dat %>%
#'   filter(County_name %in% "Culpeper County") %>%
#'   select(NH_Asian_alone_CEN_2010, County_name, state, county, tract) %>%
#'   tidyr::unite(GEOID, state,county,tract, sep="", remove=TRUE) %>%
#'   mutate(GEOID = as.character(GEOID)) %>%
#'   mutate(NH_Asian_alone_CEN_2010 = as.numeric(as.character(NH_Asian_alone_CEN_2010))) %>%
#'   mutate(NAME = as.character(County_name)) %>%
#' #  mutate(NAME = substring(NAME, 1, nchar(NAME)-10)) %>%
#'   mutate(NAME = gsub(NAME, pattern = " County", replacement = ""))
#' head(dat)
#'
#' # read in Virginia counties shape file
#' va = tracts(state = "Virginia", county = "Culpeper", year = 2016) %>%
#'   st_as_sf() %>%
#'   st_transform(crs = 3857)
#'
#' # Join data and Shape data
#' va_dat <- dat %>%
#'   inner_join(va, by = c('GEOID' = 'GEOID'))
#'
#'
#' #' Quick plots of the merged data.
#' library(ggplot2)
#' g1 <- ggplot(va_dat) +
#'   geom_sf(colour = "black", size = 0.05, aes(fill = NH_Asian_alone_CEN_2010)) +
#'   scale_fill_distiller("HHI", palette = "RdYlBu") +
#'   ggtitle("NH_Asian_alone_CEN_2010", subtitle = "Culpeper County") +
#'   theme_bw()
#' print(g1)