Retail Sales: Retail (Excluding Food Services) (MRTSMPCSM44000USN)
symbol <-fredr_series_observations(series_id = "MRTSMPCSM44000USN",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,n=12) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
240
|
2019-12-01
|
11.3
|
|
241
|
2020-01-01
|
-20.0
|
|
242
|
2020-02-01
|
-0.8
|
|
243
|
2020-03-01
|
3.9
|
|
244
|
2020-04-01
|
-12.4
|
|
245
|
2020-05-01
|
22.5
|
|
246
|
2020-06-01
|
4.3
|
|
247
|
2020-07-01
|
2.5
|
|
248
|
2020-08-01
|
-0.7
|
|
249
|
2020-09-01
|
-2.8
|
|
250
|
2020-10-01
|
3.8
|
|
251
|
2020-11-01
|
-0.7
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-11-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Monthly",
y = "Percent Change from Preceding Period",
title = "Retail Sales: Retail (Excluding Food Services) (MRTSMPCSM44000USN)",
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('01-11-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Monthly",
y = "Percent Change from Preceding Period",
title = "Retail Sales: 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 Sales: New Car Dealers (MRTSMPCSM44111USN)
symbol <-fredr_series_observations(series_id = "MRTSMPCSM44111USN",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,n=12) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
240
|
2019-12-01
|
5.0
|
|
241
|
2020-01-01
|
-13.0
|
|
242
|
2020-02-01
|
3.2
|
|
243
|
2020-03-01
|
-19.9
|
|
244
|
2020-04-01
|
-15.7
|
|
245
|
2020-05-01
|
55.1
|
|
246
|
2020-06-01
|
4.9
|
|
247
|
2020-07-01
|
3.7
|
|
248
|
2020-08-01
|
1.7
|
|
249
|
2020-09-01
|
-0.1
|
|
250
|
2020-10-01
|
1.8
|
|
251
|
2020-11-01
|
-9.5
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-11-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Monthly",
y = "Percent Change from Preceding Period",
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()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-11-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Monthly",
y = "Percent Change from Preceding Period",
title = "Retail Sales: New Car Dealers (MRTSMPCSM44111USN) _ 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: Used Car Dealers (MRTSMPCSM44112USN)
symbol <-fredr_series_observations(series_id = "MRTSMPCSM44112USN",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,n=12) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
240
|
2019-12-01
|
-7.3
|
|
241
|
2020-01-01
|
3.5
|
|
242
|
2020-02-01
|
17.8
|
|
243
|
2020-03-01
|
-12.2
|
|
244
|
2020-04-01
|
-31.0
|
|
245
|
2020-05-01
|
64.4
|
|
246
|
2020-06-01
|
11.7
|
|
247
|
2020-07-01
|
3.8
|
|
248
|
2020-08-01
|
-1.3
|
|
249
|
2020-09-01
|
-9.2
|
|
250
|
2020-10-01
|
-1.3
|
|
251
|
2020-11-01
|
-8.4
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-11-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Monthly",
y = "Percent Change from Preceding Period",
title = "Retail Sales: Used Car Dealers (MRTSMPCSM44112USN)",
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('01-11-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Monthly",
y = "Percent Change from Preceding Period",
title = "Retail Sales: Used Car Dealers (MRTSMPCSM44112USN) _ 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: Automotive Parts, Accessories, and Tire Stores (MRTSMPCSM4413USN)
symbol <-fredr_series_observations(series_id = "MRTSMPCSM4413USN",
observation_start = as.Date("2019-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,n=12) %>% kable(caption = "Retail Sales: Automotive Parts, Accessories, and Tire Stores") %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
Retail Sales: Automotive Parts, Accessories, and Tire Stores
|
|
date
|
value
|
|
12
|
2019-12-01
|
-6.0
|
|
13
|
2020-01-01
|
0.7
|
|
14
|
2020-02-01
|
-3.9
|
|
15
|
2020-03-01
|
3.1
|
|
16
|
2020-04-01
|
-6.9
|
|
17
|
2020-05-01
|
21.6
|
|
18
|
2020-06-01
|
9.2
|
|
19
|
2020-07-01
|
-0.4
|
|
20
|
2020-08-01
|
-1.6
|
|
21
|
2020-09-01
|
-3.9
|
|
22
|
2020-10-01
|
1.4
|
|
23
|
2020-11-01
|
-9.1
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-11-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Quarterly",
y = "Percent Change ",
title = "Retail Sales: Automotive Parts, Accessories, and Tire Stores (MRTSMPCSM4413USN)",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Retail Sales: Furniture Stores (MRTSMPCSM4421USN)
symbol <-fredr_series_observations(series_id = "MRTSMPCSM4413USN",
observation_start = as.Date("2019-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,n=12) %>% kable(caption = "Retail Sales at Furniture Stores") %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
Retail Sales at Furniture Stores
|
|
date
|
value
|
|
12
|
2019-12-01
|
-6.0
|
|
13
|
2020-01-01
|
0.7
|
|
14
|
2020-02-01
|
-3.9
|
|
15
|
2020-03-01
|
3.1
|
|
16
|
2020-04-01
|
-6.9
|
|
17
|
2020-05-01
|
21.6
|
|
18
|
2020-06-01
|
9.2
|
|
19
|
2020-07-01
|
-0.4
|
|
20
|
2020-08-01
|
-1.6
|
|
21
|
2020-09-01
|
-3.9
|
|
22
|
2020-10-01
|
1.4
|
|
23
|
2020-11-01
|
-9.1
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-11-2020'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Quarterly",
y = "Percent Change ",
title = "Retail Sales: Furniture Stores (MRTSMPCSM4421USN)",
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
|
|
42
|
2019-04-01
|
37978
|
|
43
|
2019-07-01
|
37895
|
|
44
|
2019-10-01
|
39742
|
|
45
|
2020-01-01
|
37558
|
|
46
|
2020-04-01
|
33377
|
|
47
|
2020-07-01
|
36623
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-11-2020'), 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('01-11-2020'), 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
|
|
42
|
2019-04-01
|
272023
|
|
43
|
2019-07-01
|
272186
|
|
44
|
2019-10-01
|
282083
|
|
45
|
2020-01-01
|
268931
|
|
46
|
2020-04-01
|
229776
|
|
47
|
2020-07-01
|
269172
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-11-2020'), 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('01-11-2020'), 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
|
|
42
|
2019-04-01
|
10311
|
|
43
|
2019-07-01
|
10032
|
|
44
|
2019-10-01
|
10824
|
|
45
|
2020-01-01
|
10796
|
|
46
|
2020-04-01
|
7735
|
|
47
|
2020-07-01
|
8921
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-11-2020'), 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('01-11-2020'), 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()
