All Employees: Leisure and Hospitality in California (CALEIH)

indicator <- fredr(series_id = "CALEIH", observation_start = as.Date("2019-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-09-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), 
                              color = "red4") +
    labs(title = "Employment: Leisure and Hospitality in California", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Thousands of Persons",
       caption = "Data source: FRED St. Louis Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="All Employment",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)}"), align = "center") %>%
     hc_title(text = "Employment: Leisure and Hospitality in California ",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED St. Louis Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Thousands of Persons")) %>%
    hc_add_theme(hc_theme_economist())

All Employees: Full-Service Restaurants in California (SMU06000007072251101)

indicator <- fredr(series_id = "SMU06000007072251101", observation_start = as.Date("2019-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
    geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-09-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
    labs(title = "Employment: Full-Service Restaurants in California", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Thousands of Persons",
       caption = "Data source: FRED St. Louis Federal Reserve\nIllustration by @JoeLongSanDiego")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="All Employment",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)}"), align = "center") %>%
     hc_title(text = "Employment: Full-Service Restaurants in California ",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED St. Louis Federal Reserve\nIllustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Thousands of Persons")) %>%
    hc_add_theme(hc_theme_economist())

All Employees: Drinking Places (Alcoholic Beverages) in California (SMU06000007072240001)

indicator <- fredr(series_id = "SMU06000007072240001", observation_start = as.Date("2019-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
    geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-09-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
    labs(title = "Employment: Drinking Places (Alcoholic Beverages) in California", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Thousands of Persons",
       caption = "Data source: FRED St. Louis Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="All Employment",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)}"), align = "center") %>%
     hc_title(text = "Employment: Drinking Places (Alcoholic Beverages) in California ",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED St. Louis Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Thousands of Persons")) %>%
    hc_add_theme(hc_theme_economist())

All Employees: Restaurants and Other Eating Places in California (SMU06000007072250001)

This industry comprises establishments primarily engaged in one of the following: (1) providing food services to patrons who order and are served while seated (i.e., waiter/waitress service), and pay after eating; (2) providing food services to patrons who generally order or select items (e.g., at a counter, in a buffet line) and pay before eating; or (3) preparing and/or serving a specialty snack (e.g., ice cream, frozen yogurt, cookies) and/or nonalcoholic beverages (e.g., coffee, juices, sodas) for consumption on or near the premises.

indicator <- fredr(series_id = "SMU06000007072250001", observation_start = as.Date("2019-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
      geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-09-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
    labs(title = "Employment: Restaurants and Other Eating Places  in California", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Thousands of Persons",
       caption = "Data source: FRED St. Louis Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="All Employment",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)}"), align = "center") %>%
     hc_title(text = "Employment: Restaurants and Other Eating Places  in California ",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Thousands of Persons")) %>%
    hc_add_theme(hc_theme_economist())

### All Employees: Limited-Service Restaurants and Other Eating Places in California (SMU06000007072259001)

This U.S. industry comprises establishments primarily engaged in providing food services (except snack and nonalcoholic beverage bars) where patrons generally order or select items and pay before eating. Food and drink may be consumed on premises, taken out, or delivered to the customer’s location. Some establishments in this industry may provide these food services in combination with selling alcoholic beverages.

This industry is comprised of: Carryout restaurants Delicatessen restaurants Drive-in restaurants Family restaurants, limited-service Fast-food restaurants Pizza delivery shops Pizza parlors, limited-service Pizzerias, limited-service (e.g., take-out) Restaurants, carryout Restaurants, fast food Sandwich shops, limited-service Steak houses, limited-service Take out eating places

indicator <- fredr(series_id = "SMU06000007072259001", observation_start = as.Date("2019-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
     geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-09-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), color = "blue4") +
    labs(title = "Employment: Fast Restaurants and Other Carryout Eating Places  in California", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Thousands of Persons",
       caption = "Data source: FRED St. Louis Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="All Employment",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)}"), align = "center") %>%
     hc_title(text = "Employment:  Fast Restaurants and Other Carryout Eating Places in California ",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Thousands of Persons")) %>%
    hc_add_theme(hc_theme_economist())

All Employees: Special Food Services in California (SMU06000007072230001)

7223 - Special Food Services This industry group comprises establishments primarily engaged in providing food services at one or more of the following locations: (1) the customer’s location (2) a location designated by the customer or (3) from motorized vehicles or nonmotorized carts.

indicator <- fredr(series_id = "SMU06000007072230001", observation_start = as.Date("2019-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
     geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-09-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), color = "blue4") +
    labs(title = "Employment: Food Catering and Mobile Eating Places  in California", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Thousands of Persons",
       caption = "Data source: FRED St Louis Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="All Employment",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)}"), align = "center") %>%
     hc_title(text = "Employment:  Food Catering and Mobile Eating Places in California ",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Thousands of Persons")) %>%
    hc_add_theme(hc_theme_economist())

### All Employees: Retail Trade: Beer, Wine, and Liquor Stores in California (SMU06000004244530001)

indicator <- fredr(series_id = "SMU06000004244530001", observation_start = as.Date("2019-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
      geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-09-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), color = "blue4") +
    labs(title = "Employment: Retail: Beer, Wine, and Liquor Stores in California", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Thousands of Persons",
       caption = "Data source: FRED St. Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="All Employment",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)}"), align = "center") %>%
     hc_title(text = "Employment: Retail: Beer, Wine, and Liquor Stores in California ",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Thousands of Persons")) %>%
    hc_add_theme(hc_theme_economist())

All Employees: Child Day Care Services in California (SMU06000006562440001)

indicator <- fredr(series_id = "SMU06000006562440001", observation_start = as.Date("2019-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
     geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-09-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), color = "blue4") +
    labs(title = "Employment: Child Day Care Services in California", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Thousands of Persons",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="All Employment",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)}"), align = "center") %>%
     hc_title(text = "Employment: Child Day Care Services in California ",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Thousands of Persons")) %>%
    hc_add_theme(hc_theme_economist())

E-Commerce Retail Sales as a Percent of Total Sales (ECOMPCTSA)

E-commerce sales are sales of goods and services where the buyer places an order, or the price and terms of the sale are negotiated over an Internet, mobile device (M-commerce), extranet, Electronic Data Interchange (EDI) network, electronic mail, or other comparable online system. Payment may or may not be made online.

indicator <- fredr(series_id = "ECOMPCTSA", observation_start = as.Date("2019-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
     geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-09-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), color = "blue4") +
    labs(title = "E-Commerce Retail Sales as a Percent of Total Sales ", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Quarterly", y="Percent",
       caption = "Data source: FRED St. Louis Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="Percent",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)}"), align = "center") %>%
     hc_title(text = "E-Commerce Retail Sales as a Percent of Total Sales",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Percent")) %>%
    hc_add_theme(hc_theme_economist())

Advance Retail Sales: Retail (Excluding Food Services) (RSXFS)

indicator <- fredr(series_id = "RSXFS", observation_start = as.Date("2019-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
     geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-09-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), color = "blue4") +
    labs(title = "Advance Retail Sales: Retail (Excluding Food Services) ", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Monthly", y="Millions of Dollars",
       caption = "Data source: FRED St. Louis Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="Millions of Dollars",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)}"), align = "center") %>%
     hc_title(text = "Advance Retail Sales: Retail (Excluding Food Services)",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED St. Louis Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "")) %>%
    hc_add_theme(hc_theme_economist())