Employment Level - Service Occupations (LNU02032204)
end_date <- dmy('01-07-2021')
indicator <-fredr_series_observations(series_id = "LNU02032204",
observation_start = as.Date("2015-01-01"))
# plotting data
ggplot(indicator) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(mapping = aes(x=date,y=value/1000), color = "red4") +
labs(title = "Employment Level - Service Occupations (LNU02032204)",
subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
x="Weekly", y="Millions of Persons",
caption = "Data source: FRED Federal Reserve Bank of St. Louis.\nIllustration by @JoeLongSanDiego")+
theme_economist()
Employment Level - Sales and Office Occupations (LNU02032205)
indicator <-fredr_series_observations(series_id = "LNU02032205",
observation_start = as.Date("2015-01-01"))
# plotting data
ggplot(indicator) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(mapping = aes(x=date,y=value/1000), color = "red4") +
labs(title = "Employment Level - Sales and Office Occupations (LNU02032205)",
subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Persons",
caption = "Data source: FRED Federal Reserve Bank of St. Louis.\nIllustration by @JoeLongSanDiego")+
theme_economist()
Employment Level - Installation, Maintenance, and Repair Occupations (LNU02032211)
indicator <-fredr_series_observations(series_id = "LNU02032211",
observation_start = as.Date("2015-01-01"))
# plotting data
ggplot(indicator) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(mapping = aes(x=date,y=value/1000), color = "red4") +
labs(title = "Employment Level - Installation, Maintenance, and Repair Occupations",
subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
x="Weekly", y="Millions of Persons",
caption = "Data source: FRED Federal Reserve Bank of St. Louis.\nIllustration by @JoeLongSanDiego")+
theme_economist()
Employment Level - Construction and Extraction Occupations (LNU02032210)
indicator <-fredr_series_observations(series_id = "LNU02032210",
observation_start = as.Date("2015-01-01"))
# plotting data
ggplot(indicator) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(mapping = aes(x=date,y=value/1000), color = "red4") +
labs(title = "Employment Level - Construction and Extraction Occupations (LNU02032210)",
subtitle = str_glue("Monthly from {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Persons",
caption = "Data source: FRED Federal Reserve Bank of St. Louis.\nIllustration by @JoeLongSanDiego")+
theme_economist()
Employment Level - Transportation and Material Moving Occupations (LNU02032214)
indicator <-fredr_series_observations(series_id = "LNU02032214",
observation_start = as.Date("2015-01-01"))
# plotting data
ggplot(indicator) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(mapping = aes(x=date,y=value/1000), color = "red4") +
labs(title = "Employment Level - Transportation and Material Moving Occupations (LNU02032214)",
subtitle = str_glue("Monthly from {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Persons",
caption = "Data source: FRED Federal Reserve Bank of St. Louis.\nIllustration by @JoeLongSanDiego")+
theme_economist()
Employment Level - Production Occupations (LNU02032213)
indicator <-fredr_series_observations(series_id = "LNU02032213",
observation_start = as.Date("2015-01-01"))
# plotting data
ggplot(indicator) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(mapping = aes(x=date,y=value/1000), color = "red4") +
labs(title = "Employment Level - Production Occupations (LNU02032213)",
subtitle = str_glue("Monthly from {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Millions of Persons",
caption = "Data source: FRED Federal Reserve Bank of St. Louis.\nIllustration by @JoeLongSanDiego")+
theme_economist()
New Unemployment Insured Claims in California
ca_claims <-
"CAICLAIMS" %>%
tq_get(get = "economic.data",
from = "2019-01-01") %>%
rename(claims = price)
## Registered S3 method overwritten by 'tune':
## method from
## required_pkgs.model_spec parsnip
ca_claims %>%
ggplot(aes(x = date, y = claims)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(color = "blue",size=1) +
labs(
x = "",
y = "",
title = "New Unemployment Claims _ California",
caption = "Data source: FRED Philadelphia Federal Reserve\nIllustration by @JoeLongSanDiego",
subtitle = str_glue("{min(ca_claims$date)} through {max(ca_claims$date)}")
) +
theme_economist() +
scale_y_continuous(labels = scales::comma)
California
library(lubridate)
library(dplyr)
ca_claims$year <- year(ca_claims$date)
ca_claims$month <- month(ca_claims$date)
ca_claims$week <- week(ca_claims$date)
ca_month <- ca_claims %>%
group_by(year,month)%>%
summarise(count =sum(claims))
## `summarise()` has grouped output by 'year'. You can override using the `.groups` argument.
ggplot(data=ca_month,aes(x=reorder(month,year),y = count,fill=month)) +
geom_bar(stat = "identity")+
labs( title = "New Unemployment Claims in California",
subtitle = str_glue("Monthly from {min(ca_month$year)} through {max(ca_month$year)}\nSeptember 2020 is unfinished"),
caption = "Data source: FRED Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego",
y = "", x = "")
ca_month %>%
kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(3, T, color = "blue" ) %>%
column_spec(1:2, T, color = "green" )
|
year
|
month
|
count
|
|
2019
|
1
|
197785
|
|
2019
|
2
|
171719
|
|
2019
|
3
|
201469
|
|
2019
|
4
|
159868
|
|
2019
|
5
|
153713
|
|
2019
|
6
|
201622
|
|
2019
|
7
|
152034
|
|
2019
|
8
|
181829
|
|
2019
|
9
|
133808
|
|
2019
|
10
|
153780
|
|
2019
|
11
|
211487
|
|
2019
|
12
|
180199
|
|
2020
|
1
|
199167
|
|
2020
|
2
|
203952
|
|
2020
|
3
|
1345649
|
|
2020
|
4
|
2427989
|
|
2020
|
5
|
1205251
|
|
2020
|
6
|
1059116
|
|
2020
|
7
|
1083952
|
|
2020
|
8
|
1031385
|
|
2020
|
9
|
866807
|
|
2020
|
10
|
788828
|
|
2020
|
11
|
615167
|
|
2020
|
12
|
710505
|
|
2021
|
1
|
628333
|
|
2021
|
2
|
456985
|
|
2021
|
3
|
418498
|
|
2021
|
4
|
302312
|
|
2021
|
5
|
354027
|
|
2021
|
6
|
241058
|
|
2021
|
7
|
115772
|
Unemployment Rate in San Diego County, CA (CASAND5URN)
sdurn <-
"CASAND5URN" %>%
tq_get(get = "economic.data",
from = "2019-01-01") %>%
rename(claims = price)
sdurn %>%
ggplot(aes(x = date, y = claims)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(color = "blue",size=1) +
labs(
x = "",
y = "",
title = "Unemployment Rate _ San Diego (CASAND5URN)",
subtitle = str_glue("From {min(sdurn$date)} through {max(sdurn$date)}"),
caption = "Data source: FRED Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego") +
theme_economist() +
scale_y_continuous(labels = scales::comma)
sdun <-
"LAUCN060730000000004" %>%
tq_get(get = "economic.data",
from = "2019-01-01") %>%
rename(claims = price)
sdun %>%
ggplot(aes(x = date, y = claims)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(color = "blue",size=1) +
labs(
x = "",
y = "",
title = "Unemployment Population _ San Diego (LAUCN060730000000004)",
subtitle = str_glue("From {min(sdun$date)} through {max(sdun$date)}"),
caption = "Data source: FRED Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego") +
theme_economist() +
scale_y_continuous(labels = scales::comma)
sdlabor <-
"CASAND5LFN" %>%
tq_get(get = "economic.data",
from = "2019-01-01") %>%
rename(claims = price)
sdlabor %>%
ggplot(aes(x = date, y = claims)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(color = "blue",size=1) +
labs(
x = "",
y = "Persons",
title = "Civilian Labor Force in San Diego County, CA (CASAND5LFN)",
subtitle = str_glue("From {min(sdlabor$date)} through {max(sdlabor$date)}"),
caption = "Data source: FRED Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego") +
theme_economist() +
scale_y_continuous(labels = scales::comma)
Unemployment Rate in Riverside County, CA (CARIVE5URN)
Unemployed Persons in Riverside County, CA (LAUCN060650000000004)
rsurn <-
"CARIVE5URN" %>%
tq_get(get = "economic.data",
from = "2019-01-01") %>%
rename(claims = price)
rsurn %>%
ggplot(aes(x = date, y = claims)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(color = "darkgreen",size=1) +
labs(
x = "",
y = "Rate",
title = "Unemployment Rate _ Riverside County (CARIVE5URN)",
subtitle = str_glue("From {min(rsurn$date)} through {max(rsurn$date)}"),
caption = "Data source: FRED Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego") +
theme_economist()+
scale_y_continuous(labels = scales::comma)
rsun <-
"LAUCN060650000000004" %>%
tq_get(get = "economic.data",
from = "2019-01-01") %>%
rename(claims = price)
rsun %>%
ggplot(aes(x = date, y = claims)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(color = "darkgreen",size=1) +
labs(
x = "",
y = "Persons",
title = "Unemployment Population _ Riverside County (LAUCN060650000000004)",
subtitle = str_glue("From {min(rsun$date)} through {max(rsun$date)}"),
caption = "Data source: FRED Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego") +
theme_economist()+
scale_y_continuous(labels = scales::comma)
#---------------------
rslabor <-
"CARIVE5LFN" %>%
tq_get(get = "economic.data",
from = "2019-01-01") %>%
rename(claims = price)
rslabor %>%
ggplot(aes(x = date, y = claims)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(color = "darkgreen",size=1) +
labs(
x = "",
y = "Persons",
title = "Civilian Labor Force in Riverside County, CA (CARIVE5LFN)",
subtitle = str_glue("From {min(rslabor$date)} through {max(rslabor$date)}"),
caption = "Data source: FRED Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego") +
theme_economist()+
scale_y_continuous(labels = scales::comma)
Unemployment Rate in Orange County, CA (CAORAN7URN)
Unemployed Persons in Orange County, CA (LAUCN060590000000004)
Civilian Labor Force in Orange County, CA (CAORAN7LFN)
ocurn <-
"CAORAN7URN" %>%
tq_get(get = "economic.data",
from = "2019-01-01") %>%
rename(claims = price)
ocurn %>%
ggplot(aes(x = date, y = claims)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(color = "blue",size=1) +
labs(
x = "",
y = "",
title = "Unemployment Rate _ Orange County (CAORAN7URN)",
subtitle = str_glue("From {min(ocurn$date)} through {max(ocurn$date)}"),
caption = "Data source: FRED Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego") +
theme_economist()+
scale_y_continuous(labels = scales::comma)
#--------------------------------
ocun <-
"LAUCN060590000000004" %>%
tq_get(get = "economic.data",
from = "2019-01-01") %>%
rename(claims = price)
ocun %>%
ggplot(aes(x = date, y = claims)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(color = "blue",size=1) +
labs(
x = "",
y = "",
title = "Unemployment Population _ Orange County (LAUCN060590000000004)",
subtitle = str_glue("From {min(ocun$date)} through {max(ocun$date)}"),
caption = "Data source: FRED Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego") +
theme_economist()+
scale_y_continuous(labels = scales::comma)
#------------------------
oclabor <-
"CAORAN7LFN" %>%
tq_get(get = "economic.data",
from = "2019-01-01") %>%
rename(claims = price)
oclabor %>%
ggplot(aes(x = date, y = claims)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(color = "blue",size=1) +
labs(
x = "",
y = "",
title = "Civilian Labor Force in Orange County, CA (CAORAN7LFN)",
subtitle = str_glue("From {min(oclabor$date)} through {max(oclabor$date)}"),
caption = "Data source: FRED Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego") +
theme_economist()+
scale_y_continuous(labels = scales::comma)
Unemployment Rate in Los Angeles County, CA (CALOSA7URN)
Unemployed Persons in Los Angeles County, CA (LAUCN060370000000004)
Civilian Labor Force in Orange County, CA (CALOSA7LFN)
laurn <-
"CALOSA7URN" %>%
tq_get(get = "economic.data",
from = "2019-01-01") %>%
rename(claims = price)
laurn %>%
ggplot(aes(x = date, y = claims)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(color = "darkblue",size=1) +
labs(
x = "",
y = "",
title = "Unemployment Rate _ Los Angeles County (CALOSA7URN)",
subtitle = str_glue("From {min(laurn$date)} through {max(laurn$date)}"),
caption = "Data source: FRED Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego") +
theme_economist() +
scale_y_continuous(labels = scales::comma)
#--------------------------------
laun <-
"LAUCN060370000000004" %>%
tq_get(get = "economic.data",
from = "2019-01-01") %>%
rename(claims = price)
laun %>%
ggplot(aes(x = date, y = claims)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(color = "darkblue",size=1) +
labs(
x = "",
y = "",
title = "Unemployment Population _ Los Angeles County (LAUCN060370000000004)",
subtitle = str_glue("From {min(laun$date)} through {max(laun$date)}"),
caption = "Data source: FRED Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego") +
theme_economist() +
scale_y_continuous(labels = scales::comma)
#------------------------
lalabor <-
"CALOSA7LFN" %>%
tq_get(get = "economic.data",
from = "2019-01-01") %>%
rename(claims = price)
oclabor %>%
ggplot(aes(x = date, y = claims)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=end_date, ymin = -Inf, ymax = Inf),
fill = "lightyellow", alpha = 0.02)+
geom_line(color = "blue",size=1) +
labs(
x = "",
y = "",
title = "Civilian Labor Force in Los Angeles County, CA (CALOSA7LFN)",
subtitle = str_glue("From {min(lalabor$date)} through {max(lalabor$date)}"),
caption = "Data source: FRED Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego") +
theme_economist()
