jobs friday

gistfile1.txt

library(tidyverse)
library(tidyquant)
library(timetk)
library(readxl)
library(plotly)
library(scales)
library(fredr)
library(broom)
library(treasuryTR)
# library(modeltime)
# library(tidymodels)
library(ppsr)
library(fredr)


employment_fred_codes <-  c(
    "NPPTTL",
    "PAYEMS",
    "USCONS",
    "USTRADE",
    "USPBS",
    "MANEMP",
    "USFIRE",
    "USMINE",
    "USEHS",
    "USWTRADE",
    "USTPU",
    "USINFO",
    "USLAH",
    "USGOVT",
    "USSERV"
  )


get_employment_from_fred <- function(fred_code){
  
  series_meta_data <- 
    fredr_series(fred_code)
  
  fred_code %>% 
    tq_get(get = "economic.data", from = "2000-01-01") %>% 
    rename(fred_code = symbol) %>% 
    arrange(desc(date)) %>% 
    left_join(series_meta_data %>% rename(fred_code = id)) %>% 
    relocate(fred_code, title, date, everything()) %>%
  select(fred_code, title, date, price, frequency) %>% 
  mutate(title = str_remove_all(title, "All Employees, ") %>% str_to_lower(),
         title = str_replace(title, "total nonfarm private payroll employment", "ADP")) %>% 
  # mutate(title = str_glue("{title}_thous_employees")) %>% 
  # rename(!!.$title[1] := 4) %>% 
  select(title, fred_code, date, employees_thous = price)  %>% 
  group_by(fred_code) %>% 
 # filter(date == ymd(start_date_chosen) + months(1) |
 #           date == ymd(start_date_chosen)) %>% 
  arrange(date) %>% 
  mutate(perc_change = employees_thous/lag(employees_thous) - 1,
         change= employees_thous-lag(employees_thous))
  
}

empl_change_2021 <- 
map_dfr(employment_fred_codes[1:15], 
        get_employment_from_fred)

start_date_chosen <- "2021-10-01"

 empl_change_2021 %>% 
  filter(date == start_date_chosen) %>% 
  ggplot(aes(x = reorder(title, change), y = change, fill = title)) + 
  geom_col(show.legend = F, width = .6) + 
  theme_minimal() +
  scale_y_continuous(label = comma_format(suffix = "K"),
                     breaks = pretty_breaks(n= 10)) + 
  labs(x = "", 
       y = "", 
       title = str_glue("Total Jobs Added {month(ymd(start_date_chosen), label = T, abbr = F)} 2021"),
       expand = c(0, 150)) +
   geom_text(aes(label = ifelse(abs(change) < 0.03 * max(change), "", 
                              number_format( 
                                accuracy = 1,
                                     big.mark=",", 
                                     suffix = "K")(change)), 
                 y = 0.6 * change),
            colour = "white", size = 2.8) +
  coord_flip()