Retail Sales: Grocery Stores (MRTSSM4451USS) Source: U.S. Census Bureau Release: Monthly Retail Trade and Food Services
Units: Millions of Dollars, Seasonally Adjusted
Frequency: Monthly
Suggested Citation: U.S. Census Bureau, Retail Sales: Grocery Stores [MRTSSM4451USS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MRTSSM4451USS, August 24, 2020.
Retail Sales: Beer, Wine, and Liquor Stores (MRTSSM4453USS) Source: U.S. Census Bureau Release: Monthly Retail Trade and Food Services
Units: Millions of Dollars, Seasonally Adjusted
Frequency: Monthly
Information about the Monthly Retail Trade Survey can be found on the Census website at https://www.census.gov/retail/mrts/about_the_surveys.html
Suggested Citation: U.S. Census Bureau, Retail Sales: Beer, Wine, and Liquor Stores [MRTSSM4453USS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MRTSSM4453USS, August 24, 2020.
Retail Sales: Pharmacies and Drug Stores (MRTSSM44611USS) Source: U.S. Census Bureau Release: Monthly Retail Trade and Food Services
Units: Millions of Dollars, Seasonally Adjusted
Frequency: Monthly
Suggested Citation: U.S. Census Bureau, Retail Sales: Pharmacies and Drug Stores [MRTSSM44611USS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MRTSSM44611USS, August 24, 2020.
Retail Sales: Men’s Clothing Stores (MRTSSM44811USS) Source: U.S. Census Bureau Release: Monthly Retail Trade and Food Services
Units: Millions of Dollars, Seasonally Adjusted
Frequency: Monthly
Information about the Monthly Retail Trade Survey can be found on the Census website at https://www.census.gov/retail/mrts/about_the_surveys.html
Suggested Citation: U.S. Census Bureau, Retail Sales: Men’s Clothing Stores [MRTSSM44811USS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MRTSSM44811USS, August 24, 2020.
Retail Sales: Sporting Goods, Hobby, Book, and Music Stores (MRTSSM451USS) Source: U.S. Census Bureau Release: Monthly Retail Trade and Food Services
Units: Millions of Dollars, Seasonally Adjusted
Frequency: Monthly
The most recent month’s value of the advance estimate based on data from a subsample of firms from the larger Monthly Retail Trade Survey is available at https://fred.stlouisfed.org/series/RSSGHBMS
Information about the Monthly Retail Trade Survey can be found on the Census website at https://www.census.gov/retail/mrts/about_the_surveys.html
Suggested Citation: U.S. Census Bureau, Retail Sales: Sporting Goods, Hobby, Book, and Music Stores [MRTSSM451USS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MRTSSM451USS, August 24, 2020.
Retail Sales: Warehouse Clubs and Superstores (MRTSSM45291USS) Source: U.S. Census Bureau Release: Monthly Retail Trade and Food Services
Units: Millions of Dollars, Seasonally Adjusted
Frequency: Monthly
Information about the Monthly Retail Trade Survey can be found on the Census website at https://www.census.gov/retail/mrts/about_the_surveys.html
Suggested Citation: U.S. Census Bureau, Retail Sales: Warehouse Clubs and Superstores [MRTSSM45291USS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MRTSSM45291USS, August 24, 2020.
Retail Sales: Electronic Shopping and Mail-order Houses (MRTSSM4541USS) Source: U.S. Census Bureau Release: Monthly Retail Trade and Food Services
Units: Millions of Dollars, Seasonally Adjusted
Frequency: Monthly
Information about the Monthly Retail Trade Survey can be found on the Census website at https://www.census.gov/retail/mrts/about_the_surveys.html
Suggested Citation: U.S. Census Bureau, Retail Sales: Electronic Shopping and Mail-order Houses [MRTSSM4541USS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MRTSSM4541USS, August 24, 2020.
# Retail Sales: Gasoline Stations (MRTSSM447USN)
indicator <-fredr_series_observations(series_id = "MRTSSM447USN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Gasoline Retail Stations",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve \n Illustration by @JoeLongSanDiego")+
theme_economist()
indicator <-fredr_series_observations(series_id = "MRTSSM4521EUSN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = " Department Stores _ Retail sales",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
theme_economist()
indicator <-fredr_series_observations(series_id = "MRTSSM44111USN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "New car sales at dealerships",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
theme_economist()
indicator <-fredr_series_observations(series_id = "MRTSSM44112USN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Used car sales at dealerships",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
theme_economist()
# Retail Sales: Retail and Food Services, Total (MRTSSM44X72USS)
indicator <-fredr_series_observations(series_id = "MRTSSM44X72USS",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Retail and Food Services",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
theme_economist()
indicator <-fredr_series_observations(series_id = "MRTSSM4453USN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Beer, Wine, and Liquor Stores",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
theme_economist()
indicator <-fredr_series_observations(series_id = "MRTSSM7225USN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Restaurants and Other Eating Places",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
theme_economist()
indicator <-fredr_series_observations(series_id = "MRTSSM4451USS",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Grocery Stores",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve \nIllustration by @JoeLongSanDiego")+
theme_economist()
indicator <-fredr_series_observations(series_id = "MRTSSM442USN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Furniture and Home Furnishings Stores",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve \nIllustration by @JoeLongSanDiego")+
theme_economist()
indicator <-fredr_series_observations(series_id = "MRTSSM4481USN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Clothing Stores",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve \nIllustration by @JoeLongSanDiego")+
theme_economist()
indicator <-fredr_series_observations(series_id = "MRTSSM45111USN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Sporting Goods Retrail Stores",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve \nIllustration by @JoeLongSanDiego")+
theme_economist()
indicator <-fredr_series_observations(series_id = "MRTSSM722USN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Food Services and Drinking Places Retail Stores",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve \nIllustration by @JoeLongSanDiego")+
theme_economist()
indicator <-fredr_series_observations(series_id = "MRTSSM45111USN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Sporting Goods Retail Stores",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
theme_economist()
indicator <-fredr_series_observations(series_id = "MRTSSM45111USN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Sporting Goods Retail Stores",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
theme_economist()
# Retail Sales: Supermarkets and Other Grocery (Except Convenience) Stores (MRTSSM44511USN)
indicator <-fredr_series_observations(series_id = "MRTSSM44511USN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Supermarkets and Other Grocery (Except Convenience)",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
theme_economist()
indicator <-fredr_series_observations(series_id = "MRTSSM444USN",
observation_start = as.Date("2019-01-01"))
indicator %>% ggplot() +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-04-2021'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_line(mapping = aes(x=date,y=value),color="red",size=1) +
labs(title = "Building Materials, Garden Equipment and Supplies Dealers",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
theme_economist()
#------------------------
symbol1 <-fredr_series_observations(series_id = "MRTSSM4451USS",
observation_start = as.Date("2019-01-01"))
indicator1 <-as.data.frame(symbol1)[,c(1,3)]
symbol2 <-fredr_series_observations(series_id = "MRTSSM4453USS",
observation_start = as.Date("2019-01-01"))
indicator2 <-as.data.frame(symbol2)[,c(1,3)]
indicator <-full_join(symbol1,symbol2, by="date")
indicator <- indicator[,c(1,3,5)]
colnames(indicator) <- c("date","Grocery_Store","Liquor_Store")
#------------------------
indicator %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(1:3, T, color = "blue" )
date | Grocery_Store | Liquor_Store |
---|---|---|
2019-01-01 | 57299 | 2021-06-10 |
2019-02-01 | 55865 | 2021-06-10 |
2019-03-01 | 57045 | 2021-06-10 |
2019-04-01 | 57255 | 2021-06-10 |
2019-05-01 | 57417 | 2021-06-10 |
2019-06-01 | 57849 | 2021-06-10 |
2019-07-01 | 58581 | 2021-06-10 |
2019-08-01 | 58549 | 2021-06-10 |
2019-09-01 | 58117 | 2021-06-10 |
2019-10-01 | 58172 | 2021-06-10 |
2019-11-01 | 58406 | 2021-06-10 |
2019-12-01 | 58877 | 2021-06-10 |
2020-01-01 | 58546 | 2021-06-10 |
2020-02-01 | 58441 | 2021-06-10 |
2020-03-01 | 75026 | 2021-06-10 |
2020-04-01 | 65033 | 2021-06-10 |
2020-05-01 | 65931 | 2021-06-10 |
2020-06-01 | 64685 | 2021-06-10 |
2020-07-01 | 64944 | 2021-06-10 |
2020-08-01 | 63861 | 2021-06-10 |
2020-09-01 | 63823 | 2021-06-10 |
2020-10-01 | 63383 | 2021-06-10 |
2020-11-01 | 64371 | 2021-06-10 |
2020-12-01 | 63775 | 2021-06-10 |
2021-01-01 | 64656 | 2021-06-10 |
2021-02-01 | 64353 | 2021-06-10 |
2021-03-01 | 64529 | 2021-06-10 |
chart <- indicator %>% ggplot() +
geom_line(mapping = aes(x=date,y=Grocery_Store),color="red",size=1) +
geom_line(mapping = aes(x=date,y=Liquor_Store),color="blue",size=1) +
labs(title = "Food and Belverages at Retail Store",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Dollars",
caption = "Data source: FRED Philadelphia Federal Reserve. Illustration by @JoeLongSanDiego")+
theme_economist()
chart + geom_text(aes(x = max(date),y=last(Grocery_Store),label="Grocery_Store"))+
geom_text(aes(x = max(date),y=last(Liquor_Store),label="Beer/Wine/Liquor_Story"))