2020 Monthly Retail Trade and Food Services During COVID Pandemic
Joe Long
10/16/2020
Retail Inventories: Retail (Excluding Food Services) (MRTSIM44000USN)
symbol <-fredr_series_observations(series_id = "MRTSIM44000USN",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2, T, color = "red" ) | date | value | |
|---|---|---|
| 243 | 2020-03-01 | 668331 |
| 244 | 2020-04-01 | 643641 |
| 245 | 2020-05-01 | 597665 |
| 246 | 2020-06-01 | 579705 |
| 247 | 2020-07-01 | 580499 |
| 248 | 2020-08-01 | 586524 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Monthly",
y = "Millions of dollars",
title = "Retail Inventories: Retail (Excluding Food Services) (MRTSIM44000USN)",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Monthly",
y = "Millions of dollars",
title = "Retail Inventories: Retail (Excluding Food Services) _ Short Term Trend",
subtitle = str_glue("From {min(indicator2$date)} through {max(indicator2$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Retail Inventories: Clothing and Clothing Accessory Stores (MRTSIM448USN)
symbol <-fredr_series_observations(series_id = "MRTSIM448USN",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2, T, color = "red" ) | date | value | |
|---|---|---|
| 243 | 2020-03-01 | 54304 |
| 244 | 2020-04-01 | 52612 |
| 245 | 2020-05-01 | 50541 |
| 246 | 2020-06-01 | 48175 |
| 247 | 2020-07-01 | 47720 |
| 248 | 2020-08-01 | 47754 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Monthly",
y = "Millions of dollars",
title = "Retail Inventories: Clothing and Clothing Accessory Stores (MRTSIM448USN)",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Monthly",
y = "Millions of dollars",
title = "Retail Inventories: Clothing and Clothing Accessory Stores _ Short Term Trend",
subtitle = str_glue("From {min(indicator2$date)} through {max(indicator2$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Retail Inventories: Department Stores (MRTSIM4521EUSS)
symbol <-fredr_series_observations(series_id = "MRTSIM4521EUSS",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2, T, color = "red" ) | date | value | |
|---|---|---|
| 243 | 2020-03-01 | 23389 |
| 244 | 2020-04-01 | 22157 |
| 245 | 2020-05-01 | 21712 |
| 246 | 2020-06-01 | 20270 |
| 247 | 2020-07-01 | 20061 |
| 248 | 2020-08-01 | 20537 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Monthly",
y = "Millions of dollars",
title = "Retail Inventories: Department Stores (MRTSIM4521EUSS)",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Monthly",
y = "Millions of dollars",
title = "Retail Inventories: Department Stores (MRTSIM4521EUSS) _ Short Term Trend",
subtitle = str_glue("From {min(indicator2$date)} through {max(indicator2$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
##Retail Sales: New Car Dealers (MRTSMPCSM44111USN)
symbol <-fredr_series_observations(series_id = "BUS5615TAXABL144QNSA",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2, T, color = "red" ) | date | value | |
|---|---|---|
| 62 | 2019-01-01 | NA |
| 63 | 2019-04-01 | NA |
| 64 | 2019-07-01 | NA |
| 65 | 2019-10-01 | NA |
| 66 | 2020-01-01 | 2960 |
| 67 | 2020-04-01 | 659 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Quarterly",
y = "Millions of Dollars",
title = " Retail Sales: New Car Dealers (MRTSMPCSM44111USN)",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Total Discharges for General Medical and Surgical Hospitals, All Establishments (DISC6221ALLEST176QNSA)
symbol <-fredr_series_observations(series_id = "DISC6221ALLEST176QNSA",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2, T, color = "red" ) | date | value | |
|---|---|---|
| 27 | 2019-01-01 | 9236 |
| 28 | 2019-04-01 | 9216 |
| 29 | 2019-07-01 | 9095 |
| 30 | 2019-10-01 | 9152 |
| 31 | 2020-01-01 | 8942 |
| 32 | 2020-04-01 | 7513 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Quarterly",
y = "Thousands of Patents",
title = " Total Discharges for General Medical and Surgical Hospitals",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Quarterly",
y = "Thousands of Patents",
title = "Total Discharges for General Medical and Surgical Hospitals _ Short Term Trend",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Total Expense for Ambulatory Health Care Services, All Establishments (EXP621ALLEST144QNSA)
symbol <-fredr_series_observations(series_id = "EXP621ALLEST144QNSA",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2, T, color = "red" ) | date | value | |
|---|---|---|
| 41 | 2019-01-01 | 226693 |
| 42 | 2019-04-01 | 234386 |
| 43 | 2019-07-01 | 235022 |
| 44 | 2019-10-01 | 247626 |
| 45 | 2020-01-01 | 233781 |
| 46 | 2020-04-01 | 205704 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Quarterly",
y = "Millions of Dollars",
title = " Total Expense for Ambulatory Health Care Services",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Quarterly",
y = "Millions of Dollars",
title = "Total Expense for Ambulatory Health Care Services _ Short Term Trend",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Total Revenue for Outpatient Care Centers, All Establishments (REV6214ALLEST144QNSA)
symbol <-fredr_series_observations(series_id = "REV6214ALLEST144QNSA",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2, T, color = "red" ) | date | value | |
|---|---|---|
| 41 | 2019-01-01 | 37014 |
| 42 | 2019-04-01 | 37978 |
| 43 | 2019-07-01 | 37895 |
| 44 | 2019-10-01 | 39742 |
| 45 | 2020-01-01 | 37558 |
| 46 | 2020-04-01 | 33418 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Quarterly",
y = "Millions of Dollars",
title = " Total Revenue for Outpatient Care Centers",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Quarterly",
y = "Millions of Dollars",
title = "Total Revenue for Outpatient Care Centers _ Short Term Trend",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Total Revenue for Ambulatory Health Care Services, All Establishments (REV621ALLEST144QNSA)
symbol <-fredr_series_observations(series_id = "REV621ALLEST144QNSA",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2, T, color = "red" ) | date | value | |
|---|---|---|
| 41 | 2019-01-01 | 262750 |
| 42 | 2019-04-01 | 272023 |
| 43 | 2019-07-01 | 272186 |
| 44 | 2019-10-01 | 282083 |
| 45 | 2020-01-01 | 268931 |
| 46 | 2020-04-01 | 230057 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Quarterly",
y = "Millions of Dollars",
title = "Total Revenue for Ambulatory Health Care Services",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Quarterly",
y = "Millions of Dollars",
title = "Total Revenue for Ambulatory Health Care Services _ Short Term Trend",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Total Expense for Child Day Care Services, All Establishments (EXP6244ALLEST144QNSA)
symbol <-fredr_series_observations(series_id = "EXP6244ALLEST144QNSA",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2, T, color = "red" ) | date | value | |
|---|---|---|
| 41 | 2019-01-01 | 10243 |
| 42 | 2019-04-01 | 10311 |
| 43 | 2019-07-01 | 10032 |
| 44 | 2019-10-01 | 10824 |
| 45 | 2020-01-01 | 10796 |
| 46 | 2020-04-01 | 7783 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Quarterly",
y = "Millions of Dollars",
title = "Total Expense for Child Day Care Services",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Quarterly",
y = "Millions of Dollars",
title = "Total Expense for Child Day Care Services _ Short Term Trend",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()