Retail Sales : 2021 to 2022
Joe Long
04/27/2022
Retail Sales: Grocery Stores (MRTSSM4451USS) Source: U.S. Census Bureau Release: Monthly Retail Trade and Food Services
Units: Millions of Dollars, Seasonally Adjusted
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,
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
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
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,
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
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,
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 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
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 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
Most recently updated on February 01, 2022
# 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('01-02-2021'), xmax=dmy('01-02-2022'), 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()
# Retail Sales: Department Stores (MRTSSM4521EUSN)
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('01-02-2022'), 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()
# Retail Sales: New Car Dealers (MRTSSM44111USN)
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('01-02-2022'), 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()
# Retail Sales: Used Car Dealers (MRTSSM44112USN)
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('01-02-2022'), 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('01-02-2022'), 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()
# Retail Sales: Beer, Wine, and Liquor Stores (MRTSSM4453USN)
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('01-02-2022'), 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()
# Retail Sales: Restaurants and Other Eating Places (MRTSSM7225USN)
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('01-02-2022'), 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()
# Retail Sales: Grocery Stores (MRTSSM4451USS)
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('01-02-2022'), 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()
# Retail Sales: Furniture and Home Furnishings Stores (MRTSSM442USN)
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('01-02-2022'), 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()
# Retail Sales: Clothing Stores (MRTSSM4481USN)
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('01-02-2022'), 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()
# Retail Sales: Sporting Goods Stores (MRTSSM45111USN)
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('01-02-2022'), 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()
# Retail Sales: Food Services and Drinking Places (MRTSSM722USN)
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('01-02-2022'), 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()
# Retail Sales: Limited Service Eating Places (MRTSSM7222USN)
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('01-02-2022'), 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('01-02-2022'), 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()
# Retail Sales: Building Materials, Garden Equipment and Supplies Dealers (MRTSSM444USN)
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('01-02-2022'), 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(2, T, color = "red" ) %>%
column_spec(3, T, color = "blue" ) | date | Grocery_Store | Liquor_Store |
|---|---|---|
| 2019-01-01 | 57299 | 2022-04-27 |
| 2019-02-01 | 55865 | 2022-04-27 |
| 2019-03-01 | 57045 | 2022-04-27 |
| 2019-04-01 | 57255 | 2022-04-27 |
| 2019-05-01 | 57417 | 2022-04-27 |
| 2019-06-01 | 57849 | 2022-04-27 |
| 2019-07-01 | 58581 | 2022-04-27 |
| 2019-08-01 | 58549 | 2022-04-27 |
| 2019-09-01 | 58117 | 2022-04-27 |
| 2019-10-01 | 58172 | 2022-04-27 |
| 2019-11-01 | 58406 | 2022-04-27 |
| 2019-12-01 | 58877 | 2022-04-27 |
| 2020-01-01 | 58546 | 2022-04-27 |
| 2020-02-01 | 58441 | 2022-04-27 |
| 2020-03-01 | 75026 | 2022-04-27 |
| 2020-04-01 | 65033 | 2022-04-27 |
| 2020-05-01 | 65931 | 2022-04-27 |
| 2020-06-01 | 64685 | 2022-04-27 |
| 2020-07-01 | 64944 | 2022-04-27 |
| 2020-08-01 | 63861 | 2022-04-27 |
| 2020-09-01 | 63823 | 2022-04-27 |
| 2020-10-01 | 63446 | 2022-04-27 |
| 2020-11-01 | 64371 | 2022-04-27 |
| 2020-12-01 | 63775 | 2022-04-27 |
| 2021-01-01 | 64656 | 2022-04-27 |
| 2021-02-01 | 64290 | 2022-04-27 |
| 2021-03-01 | 64605 | 2022-04-27 |
| 2021-04-01 | 65183 | 2022-04-27 |
| 2021-05-01 | 66098 | 2022-04-27 |
| 2021-06-01 | 66731 | 2022-04-27 |
| 2021-07-01 | 66592 | 2022-04-27 |
| 2021-08-01 | 68123 | 2022-04-27 |
| 2021-09-01 | 68515 | 2022-04-27 |
| 2021-10-01 | 69315 | 2022-04-27 |
| 2021-11-01 | 69504 | 2022-04-27 |
| 2021-12-01 | 69589 | 2022-04-27 |
| 2022-01-01 | 70245 | 2022-04-27 |
| 2022-02-01 | 69840 | 2022-04-27 |
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"))