In jjchern/laus: U.S. Local Area Unemployment Statistics

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README/README-fig-",
  cache.path = "README/README-cache-"
)

library(knitr)

# I want the README to have visible GIFs on GitHub, as
# GitHub cannot show .mp4s or other animation formats.
# I therefore hacked together a GIF animation hook for knitr.

library(animation)
ani.options(autobrowse = FALSE, interval = 1)

opts_knit$set(animation.fun = function(x, options, format = "gif") {
  x = c(knitr:::sans_ext(x), knitr:::file_ext(x))
  fig.num = options$fig.num
  format = sub("^[.]", "", format)
  fig.fname = paste0(sub(paste0(fig.num, "$"), "*", x[1]), 
                     ".", x[2])
  mov.fname = paste0(sub(paste0(fig.num, "$"), "", x[1]), ".", 
                     format)

  # order correctly
  figs <- Sys.glob(fig.fname)
  figs <- figs[order(as.numeric(stringr::str_match(figs, paste0("(\\d+)\\.", x[2]))[, 2]))]

  animation::im.convert(figs, output = mov.fname)

  sprintf("![%s](%s)", options$label, paste0(opts_knit$get("base.url"), mov.fname))
})

opts_chunk$set(cache = TRUE, message = FALSE, warning = FALSE, fig.show = "animate")

About

An R data package contains Local Area Unemployment Statistics (LAUS) from U.S. Bureau of Labor Statistics (BLS). So far it contains the following four series:

• state_year:
  • State-level employment status of the civilian noninstitutional population, annual average series (1976-2018)
• state_month_sa:
  • State-level employment status of the civilian noninstitutional population, seasonaly adjusted monthly series (1976-2019.03)
• state_month_nsa:
  • State-level employment status of the civilian noninstitutional population, not seasonaly adjusted monthly series (1976-2019.03)
• county_year:
  • County-level employment status of the civilian noninstitutional population, annual average series (1990-2018)
• county_month_nsa:
  • County-level employment status of the civilian noninstitutional population, not seasonaly adjusted monthly series (1976-2019.02)

Relevant packages

• rUnemploymentData

Installation

# install.package("remotes")
remotes::install_github("jjchern/laus@v0.0.4")

Usage

List all series

data(package = "laus")$results[,3]

List all variable names and variable labels for state_year

names(laus::state_year)

# devtools::install_github("larmarange/labelled")
labelled::var_label(laus::state_year)

Show the data frame

library(tidyverse)
laus::state_year
laus::county_year

Plot thematic maps with the unemployment data

Plot selected Series

laus::county_month_nsa %>%
    filter(year %in% c(2002:2011)) %>%
    filter(fips %in%
        c("17031", "36005", "42069", "11001")) %>%
    mutate(date = glue::glue("{year}-{month}-01")) %>%
    mutate(date = as.Date(date)) %>%
    mutate(county_name = paste0(county, ", ", state)) %>%
    ggplot(aes(x = date, y = `unemployment rate`,
               colour = county_name)) +
    geom_line() +
    annotate("rect",
             xmin = as.Date("2003-01-01"), xmax = as.Date("2004-12-01"),
             ymin = 4, ymax = Inf, alpha = 0.1) +
    annotate("rect",
             xmin = as.Date("2008-01-01"), xmax = as.Date("2010-12-01"),
             ymin = 4, ymax = Inf, alpha = 0.1) +
    labs(x = NULL, y = NULL,
         title = "Unemployment Rates of Selected Counties, 2002-2011") +
    hrbrthemes::theme_ipsum() +
    theme(legend.position = c(0.45, 0.8),
          legend.title = element_blank(),
          strip.text = element_text(hjust = 0.45))

laus::county_year %>%
    mutate(year = as.numeric(year)) %>%
    filter(year %in% c(2002:2011)) %>%
    filter(fips %in%
        c("17031", "36005", "42069", "11001")) %>%
    mutate(date = glue::glue("{year}-01-01")) %>%
    mutate(date = as.Date(date)) %>%
    mutate(county_name = paste0(county, ", ", state)) %>%
    rename(`unemployment rate` = unemployment_rate) %>%
    ggplot(aes(x = date, y = `unemployment rate`,
            colour = county_name)) +
    geom_line() +
    annotate("rect",
          xmin = as.Date("2003-01-01"), xmax = as.Date("2004-01-01"),
              ymin = 4, ymax = Inf, alpha = 0.1) +
    annotate("rect",
              xmin = as.Date("2008-01-01"), xmax = as.Date("2010-01-01"),
              ymin = 4, ymax = Inf, alpha = 0.1) +
    labs(x = NULL, y = NULL,
          title = "Unemployment Rates of Selected Counties, 2002-2011") +
    hrbrthemes::theme_ipsum() +
    theme(legend.position = c(0.45, 0.8),
          legend.title = element_blank())

library(tidyverse)
laus::state_month_nsa %>% 
    filter(state == "Illinois") %>% 
    mutate(year = factor(year)) %>% 
    mutate(month = factor(month, labels = month.abb)) %>% 
    ggplot(aes(x = year, y = month, fill = unem_rate)) +
    geom_tile(colour = "white") +
    scale_x_discrete(breaks = seq(1976, 2019, 7)) +
    viridis::scale_fill_viridis(option = "D") +
    labs(x = NULL, y = NULL) +
    labs(fill = "", title = "Illinois Monthly Unemployment Rate, 1976-2019") +
    theme(legend.position = "top",
          legend.justification = "left",
          plot.title = element_text(face = "bold", size = rel(1.4))) 

jjchern/laus documentation built on May 19, 2019, 11:38 a.m.