Business Applications for the United States (BUSAPPWNSAUS)
symbol <-fredr_series_observations(series_id = "BUSAPPWNSAUS",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,24) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
786
|
2021-01-23
|
120330
|
|
787
|
2021-01-30
|
125640
|
|
788
|
2021-02-06
|
122400
|
|
789
|
2021-02-13
|
118510
|
|
790
|
2021-02-20
|
101990
|
|
791
|
2021-02-27
|
115130
|
|
792
|
2021-03-06
|
119060
|
|
793
|
2021-03-13
|
120920
|
|
794
|
2021-03-20
|
123120
|
|
795
|
2021-03-27
|
125070
|
|
796
|
2021-04-03
|
121170
|
|
797
|
2021-04-10
|
116610
|
|
798
|
2021-04-17
|
129360
|
|
799
|
2021-04-24
|
129610
|
|
800
|
2021-05-01
|
134020
|
|
801
|
2021-05-08
|
126660
|
|
802
|
2021-05-15
|
115100
|
|
803
|
2021-05-22
|
122330
|
|
804
|
2021-05-29
|
117320
|
|
805
|
2021-06-05
|
95520
|
|
806
|
2021-06-12
|
108580
|
|
807
|
2021-06-19
|
87970
|
|
808
|
2021-06-26
|
122290
|
|
809
|
2021-07-03
|
100240
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Weekly",
y = "Count",
title = "Business Applications for United States",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator <- filter(indicator,date >= "2019-01-01")
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "",
y = "Count",
title = "Business Applications for United states _ Short Term Trend",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve.\nIllustration by @JoeLongSanDiego") +
theme_economist()
Business Applications for California (BUSAPPWNSACA)
- The core business applications series that corresponds to a subset of all EIN applications. BA includes all applications for an EIN, except for applications for tax liens, estates, trusts, or certain financial filings, applications with no state-county geocodes, applications from certain agricultural, public entities, and applications in certain industries (e.g. private households, civic and social organizations).
symbol <-fredr_series_observations(series_id = "BUSAPPWNSACA",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,24) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
786
|
2021-01-23
|
11140
|
|
787
|
2021-01-30
|
12600
|
|
788
|
2021-02-06
|
11670
|
|
789
|
2021-02-13
|
11650
|
|
790
|
2021-02-20
|
10180
|
|
791
|
2021-02-27
|
11610
|
|
792
|
2021-03-06
|
11760
|
|
793
|
2021-03-13
|
12560
|
|
794
|
2021-03-20
|
12480
|
|
795
|
2021-03-27
|
11990
|
|
796
|
2021-04-03
|
10950
|
|
797
|
2021-04-10
|
10650
|
|
798
|
2021-04-17
|
12400
|
|
799
|
2021-04-24
|
11720
|
|
800
|
2021-05-01
|
11960
|
|
801
|
2021-05-08
|
11910
|
|
802
|
2021-05-15
|
10170
|
|
803
|
2021-05-22
|
12070
|
|
804
|
2021-05-29
|
11320
|
|
805
|
2021-06-05
|
9360
|
|
806
|
2021-06-12
|
10860
|
|
807
|
2021-06-19
|
8600
|
|
808
|
2021-06-26
|
12020
|
|
809
|
2021-07-03
|
9500
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Weekly",
y = "Count",
title = "Business Applications for California",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue1",size=.8) +
labs(
x = "",
y = "Count",
title = "Business Applications for California _ Short Term Trend",
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego",
subtitle = str_glue("From {min(indicator2$date)} through {max(indicator2$date)}")
) +
theme_economist()
Business Applications from Corporations for California (CBUSAPPWNSACA)
- Business Applications from Corporations (CBA): A subset of High-Propensity Business Applications (HBA) that contains all applications that come from a corporation or a personal service corporation.
symbol <-fredr_series_observations(series_id = "CBUSAPPWNSACA",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,24) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
786
|
2021-01-23
|
2490
|
|
787
|
2021-01-30
|
3000
|
|
788
|
2021-02-06
|
2790
|
|
789
|
2021-02-13
|
2930
|
|
790
|
2021-02-20
|
2450
|
|
791
|
2021-02-27
|
2930
|
|
792
|
2021-03-06
|
3470
|
|
793
|
2021-03-13
|
3380
|
|
794
|
2021-03-20
|
3490
|
|
795
|
2021-03-27
|
3130
|
|
796
|
2021-04-03
|
2780
|
|
797
|
2021-04-10
|
2520
|
|
798
|
2021-04-17
|
2800
|
|
799
|
2021-04-24
|
2710
|
|
800
|
2021-05-01
|
2900
|
|
801
|
2021-05-08
|
2970
|
|
802
|
2021-05-15
|
2800
|
|
803
|
2021-05-22
|
3000
|
|
804
|
2021-05-29
|
2990
|
|
805
|
2021-06-05
|
2500
|
|
806
|
2021-06-12
|
2960
|
|
807
|
2021-06-19
|
2490
|
|
808
|
2021-06-26
|
3340
|
|
809
|
2021-07-03
|
2570
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Weekly",
y = "Count",
title = "Corporate Business Applications for California",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "",
y = "Count",
title = "Corporate Business Applications for California _ Short Term Trend",
subtitle = str_glue("From {min(indicator2$date)} through {max(indicator2$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
Business Applications for Oregon (BBUSAPPWNSAOR)
symbol <-fredr_series_observations(series_id = "BUSAPPWNSAOR",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,24) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
786
|
2021-01-23
|
1190
|
|
787
|
2021-01-30
|
1250
|
|
788
|
2021-02-06
|
1200
|
|
789
|
2021-02-13
|
1080
|
|
790
|
2021-02-20
|
880
|
|
791
|
2021-02-27
|
1100
|
|
792
|
2021-03-06
|
1080
|
|
793
|
2021-03-13
|
1080
|
|
794
|
2021-03-20
|
1190
|
|
795
|
2021-03-27
|
1130
|
|
796
|
2021-04-03
|
1140
|
|
797
|
2021-04-10
|
1130
|
|
798
|
2021-04-17
|
1070
|
|
799
|
2021-04-24
|
1060
|
|
800
|
2021-05-01
|
1130
|
|
801
|
2021-05-08
|
1140
|
|
802
|
2021-05-15
|
1110
|
|
803
|
2021-05-22
|
1000
|
|
804
|
2021-05-29
|
1040
|
|
805
|
2021-06-05
|
810
|
|
806
|
2021-06-12
|
930
|
|
807
|
2021-06-19
|
760
|
|
808
|
2021-06-26
|
1090
|
|
809
|
2021-07-03
|
850
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Weekly",
y = "Count",
title = "Business Applications for OREGON",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator <- filter(indicator,date >= "2019-01-01")
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "",
y = "Count",
title = "Business Applications for OREGON _ Short Term Trend",
subtitle = str_glue("From {min(indicator2$date)} through {max(indicator2$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
Business Applications for New York (BUSAPPWNSANY)
symbol <-fredr_series_observations(series_id = "BUSAPPWNSANY",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,24) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
786
|
2021-01-23
|
6760
|
|
787
|
2021-01-30
|
7130
|
|
788
|
2021-02-06
|
6460
|
|
789
|
2021-02-13
|
6550
|
|
790
|
2021-02-20
|
5650
|
|
791
|
2021-02-27
|
6250
|
|
792
|
2021-03-06
|
6860
|
|
793
|
2021-03-13
|
6910
|
|
794
|
2021-03-20
|
6880
|
|
795
|
2021-03-27
|
7020
|
|
796
|
2021-04-03
|
6790
|
|
797
|
2021-04-10
|
6860
|
|
798
|
2021-04-17
|
7140
|
|
799
|
2021-04-24
|
7050
|
|
800
|
2021-05-01
|
7200
|
|
801
|
2021-05-08
|
6810
|
|
802
|
2021-05-15
|
6390
|
|
803
|
2021-05-22
|
6100
|
|
804
|
2021-05-29
|
6510
|
|
805
|
2021-06-05
|
5070
|
|
806
|
2021-06-12
|
6030
|
|
807
|
2021-06-19
|
5170
|
|
808
|
2021-06-26
|
6150
|
|
809
|
2021-07-03
|
5330
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Weekly",
y = "Count",
title = "Business Applications for New York State",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator <- filter(indicator,date >= "2019-01-01")
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "",
y = "Count",
title = "Business Applications for New York State _ Short Term Trend",
subtitle = str_glue("From {min(indicator2$date)} through {max(indicator2$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
Business Applications for Arizona (BUSAPPWNSAAZ)
symbol <-fredr_series_observations(series_id = "BUSAPPWNSAAZ",
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(2:3, T, color = "blue" )
|
|
date
|
value
|
|
804
|
2021-05-29
|
2370
|
|
805
|
2021-06-05
|
1990
|
|
806
|
2021-06-12
|
2080
|
|
807
|
2021-06-19
|
1810
|
|
808
|
2021-06-26
|
2510
|
|
809
|
2021-07-03
|
2070
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Weekly",
y = "Count",
title = "Business Applications for ARIZONA",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "",
y = "Count",
title = "Business Applications for ARIZONA _ Short Term Trend",
subtitle = str_glue("From {min(indicator2$date)} through {max(indicator2$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
Business Applications for TEXAS (BUSAPPWNSATX)
symbol <-fredr_series_observations(series_id = "BUSAPPWNSATX",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,24) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
786
|
2021-01-23
|
10990
|
|
787
|
2021-01-30
|
11460
|
|
788
|
2021-02-06
|
12190
|
|
789
|
2021-02-13
|
10890
|
|
790
|
2021-02-20
|
5760
|
|
791
|
2021-02-27
|
8980
|
|
792
|
2021-03-06
|
9890
|
|
793
|
2021-03-13
|
10670
|
|
794
|
2021-03-20
|
10550
|
|
795
|
2021-03-27
|
11300
|
|
796
|
2021-04-03
|
11180
|
|
797
|
2021-04-10
|
10020
|
|
798
|
2021-04-17
|
12640
|
|
799
|
2021-04-24
|
10810
|
|
800
|
2021-05-01
|
12830
|
|
801
|
2021-05-08
|
11560
|
|
802
|
2021-05-15
|
10610
|
|
803
|
2021-05-22
|
10320
|
|
804
|
2021-05-29
|
10830
|
|
805
|
2021-06-05
|
8640
|
|
806
|
2021-06-12
|
9440
|
|
807
|
2021-06-19
|
8910
|
|
808
|
2021-06-26
|
12030
|
|
809
|
2021-07-03
|
9580
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Weekly",
y = "Count",
title = "Business Applications for TEXAS",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "",
y = "Count",
title = "Business Applications for TEXAS _ Short Term Trend",
subtitle = str_glue("From {min(indicator2$date)} through {max(indicator2$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
Business Applications for FLORIDA (BUSAPPWNSAFL)
symbol <-fredr_series_observations(series_id = "BUSAPPWNSAFL",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,24) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
786
|
2021-01-23
|
10980
|
|
787
|
2021-01-30
|
12740
|
|
788
|
2021-02-06
|
13320
|
|
789
|
2021-02-13
|
15320
|
|
790
|
2021-02-20
|
14630
|
|
791
|
2021-02-27
|
14960
|
|
792
|
2021-03-06
|
13980
|
|
793
|
2021-03-13
|
13820
|
|
794
|
2021-03-20
|
13290
|
|
795
|
2021-03-27
|
13890
|
|
796
|
2021-04-03
|
14020
|
|
797
|
2021-04-10
|
14660
|
|
798
|
2021-04-17
|
15050
|
|
799
|
2021-04-24
|
14380
|
|
800
|
2021-05-01
|
15700
|
|
801
|
2021-05-08
|
14670
|
|
802
|
2021-05-15
|
13570
|
|
803
|
2021-05-22
|
18900
|
|
804
|
2021-05-29
|
15940
|
|
805
|
2021-06-05
|
12690
|
|
806
|
2021-06-12
|
14570
|
|
807
|
2021-06-19
|
11170
|
|
808
|
2021-06-26
|
15530
|
|
809
|
2021-07-03
|
12380
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Weekly",
y = "Count",
title = "Business Applications for FLORIDA",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator <- filter(indicator,date >= "2019-01-01")
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "",
y = "Count",
title = "Business Applications for FLORIDA _ Short Term Trend",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
Business Applications for OKLAHOMA (BUSAPPWNSAOK)
symbol <-fredr_series_observations(series_id = "BUSAPPWNSAOK",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,24) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
786
|
2021-01-23
|
1250
|
|
787
|
2021-01-30
|
1500
|
|
788
|
2021-02-06
|
1440
|
|
789
|
2021-02-13
|
1190
|
|
790
|
2021-02-20
|
830
|
|
791
|
2021-02-27
|
1150
|
|
792
|
2021-03-06
|
1220
|
|
793
|
2021-03-13
|
1280
|
|
794
|
2021-03-20
|
1310
|
|
795
|
2021-03-27
|
1460
|
|
796
|
2021-04-03
|
1310
|
|
797
|
2021-04-10
|
1290
|
|
798
|
2021-04-17
|
1330
|
|
799
|
2021-04-24
|
1420
|
|
800
|
2021-05-01
|
1360
|
|
801
|
2021-05-08
|
1280
|
|
802
|
2021-05-15
|
1190
|
|
803
|
2021-05-22
|
1370
|
|
804
|
2021-05-29
|
1280
|
|
805
|
2021-06-05
|
1010
|
|
806
|
2021-06-12
|
1160
|
|
807
|
2021-06-19
|
810
|
|
808
|
2021-06-26
|
1290
|
|
809
|
2021-07-03
|
1070
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Weekly",
y = "Count",
title = "Business Applications for OKLAHOMA",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator <- filter(indicator,date >= "2019-01-01")
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "",
y = "Count",
title = "Business Applications for OKLAHOMA _ Short Term Trend",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
Business Applications for COLORADO (BUSAPPWNSACO)
symbol <-fredr_series_observations(series_id = "BUSAPPWNSACO",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,24) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
786
|
2021-01-23
|
2700
|
|
787
|
2021-01-30
|
2640
|
|
788
|
2021-02-06
|
2460
|
|
789
|
2021-02-13
|
2450
|
|
790
|
2021-02-20
|
2160
|
|
791
|
2021-02-27
|
2350
|
|
792
|
2021-03-06
|
2390
|
|
793
|
2021-03-13
|
2470
|
|
794
|
2021-03-20
|
2370
|
|
795
|
2021-03-27
|
2430
|
|
796
|
2021-04-03
|
2420
|
|
797
|
2021-04-10
|
2230
|
|
798
|
2021-04-17
|
2560
|
|
799
|
2021-04-24
|
2490
|
|
800
|
2021-05-01
|
2310
|
|
801
|
2021-05-08
|
2260
|
|
802
|
2021-05-15
|
2300
|
|
803
|
2021-05-22
|
2180
|
|
804
|
2021-05-29
|
2190
|
|
805
|
2021-06-05
|
1860
|
|
806
|
2021-06-12
|
2060
|
|
807
|
2021-06-19
|
1600
|
|
808
|
2021-06-26
|
2420
|
|
809
|
2021-07-03
|
2040
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Weekly",
y = "Count",
title = "Business Applications for COLORADO",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator <- filter(indicator,date >= "2019-01-01")
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "",
y = "Count",
title = "Business Applications for COLORADO _ Short Term Trend",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
Business Applications for GEORGIA (BUSAPPWNSAGA)
symbol <-fredr_series_observations(series_id = "BUSAPPWNSAGA",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,24) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
786
|
2021-01-23
|
7990
|
|
787
|
2021-01-30
|
8040
|
|
788
|
2021-02-06
|
7940
|
|
789
|
2021-02-13
|
7110
|
|
790
|
2021-02-20
|
7220
|
|
791
|
2021-02-27
|
7630
|
|
792
|
2021-03-06
|
7750
|
|
793
|
2021-03-13
|
7340
|
|
794
|
2021-03-20
|
7750
|
|
795
|
2021-03-27
|
7940
|
|
796
|
2021-04-03
|
7820
|
|
797
|
2021-04-10
|
7000
|
|
798
|
2021-04-17
|
8120
|
|
799
|
2021-04-24
|
8640
|
|
800
|
2021-05-01
|
8930
|
|
801
|
2021-05-08
|
8300
|
|
802
|
2021-05-15
|
7490
|
|
803
|
2021-05-22
|
7550
|
|
804
|
2021-05-29
|
7130
|
|
805
|
2021-06-05
|
5730
|
|
806
|
2021-06-12
|
6850
|
|
807
|
2021-06-19
|
5390
|
|
808
|
2021-06-26
|
7720
|
|
809
|
2021-07-03
|
6390
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Weekly",
y = "Count",
title = "Business Applications for GEORGIA",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator <- filter(indicator,date >= "2019-01-01")
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "",
y = "Count",
title = "Business Applications for GEORGIA _ Short Term Trend",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
Business Applications for ILLINOIS (BUSAPPWNSAIL)
symbol <-fredr_series_observations(series_id = "BUSAPPWNSAIL",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,24) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
786
|
2021-01-23
|
5140
|
|
787
|
2021-01-30
|
4790
|
|
788
|
2021-02-06
|
4860
|
|
789
|
2021-02-13
|
4500
|
|
790
|
2021-02-20
|
3860
|
|
791
|
2021-02-27
|
4570
|
|
792
|
2021-03-06
|
4840
|
|
793
|
2021-03-13
|
4730
|
|
794
|
2021-03-20
|
5130
|
|
795
|
2021-03-27
|
4910
|
|
796
|
2021-04-03
|
5110
|
|
797
|
2021-04-10
|
4870
|
|
798
|
2021-04-17
|
5470
|
|
799
|
2021-04-24
|
5760
|
|
800
|
2021-05-01
|
5800
|
|
801
|
2021-05-08
|
5080
|
|
802
|
2021-05-15
|
4220
|
|
803
|
2021-05-22
|
4460
|
|
804
|
2021-05-29
|
4060
|
|
805
|
2021-06-05
|
3420
|
|
806
|
2021-06-12
|
3670
|
|
807
|
2021-06-19
|
3070
|
|
808
|
2021-06-26
|
4210
|
|
809
|
2021-07-03
|
3630
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Weekly",
y = "Count",
title = "Business Applications for ILLINOIS",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator <- filter(indicator,date >= "2019-01-01")
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "",
y = "Count",
title = "Business Applications for ILLINOIS _ Short Term Trend",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
Business Applications for Alabama (BUSAPPWNSAAL)
symbol <-fredr_series_observations(series_id = "BUSAPPWNSAAL",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,24) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" )
|
|
date
|
value
|
|
786
|
2021-01-23
|
1830
|
|
787
|
2021-01-30
|
1880
|
|
788
|
2021-02-06
|
1800
|
|
789
|
2021-02-13
|
1680
|
|
790
|
2021-02-20
|
1460
|
|
791
|
2021-02-27
|
1600
|
|
792
|
2021-03-06
|
1790
|
|
793
|
2021-03-13
|
1730
|
|
794
|
2021-03-20
|
1740
|
|
795
|
2021-03-27
|
1850
|
|
796
|
2021-04-03
|
1750
|
|
797
|
2021-04-10
|
1770
|
|
798
|
2021-04-17
|
1940
|
|
799
|
2021-04-24
|
2230
|
|
800
|
2021-05-01
|
2190
|
|
801
|
2021-05-08
|
1950
|
|
802
|
2021-05-15
|
1630
|
|
803
|
2021-05-22
|
1740
|
|
804
|
2021-05-29
|
1630
|
|
805
|
2021-06-05
|
1300
|
|
806
|
2021-06-12
|
1600
|
|
807
|
2021-06-19
|
1260
|
|
808
|
2021-06-26
|
1780
|
|
809
|
2021-07-03
|
1360
|
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Weekly",
y = "Count",
title = "Business Applications for ALABAMA",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator <- filter(indicator,date >= "2019-01-01")
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "",
y = "Count",
title = "Business Applications for ALABAMA _ Short Term Trend",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego\nhttps://rpubs.com/Data_Panoramic/") +
theme_economist()
