Industrial and Manufacturing sectors 2020

Industrial Production Index (INDPRO) Index 2012=100, Monthly, Seasonally Adjusted

symbol <-fredr_series_observations(series_id = "INDPRO", 
      observation_start = as.Date("2019-01-01"))
      
indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
   column_spec(2, T, color = "red" ) 

date	value
2019-01-01	110.12
2019-02-01	109.56
2019-03-01	109.68
2019-04-01	108.99
2019-05-01	109.23
2019-06-01	109.28
2019-07-01	109.09
2019-08-01	109.85
2019-09-01	109.47
2019-10-01	109.03
2019-11-01	110.04
2019-12-01	109.65
2020-01-01	109.18
2020-02-01	109.30
2020-03-01	104.60
2020-04-01	91.21
2020-05-01	92.01
2020-06-01	97.22
2020-07-01	100.17

indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = "Industrial Production Index (INDPRO) Index", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Index 2012=100",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Capacity Utilization: Manufacturing (SIC) (CUMFNS) Percent of Capacity, monthly

symbol <-fredr_series_observations(series_id = "CUMFNS", 
      observation_start = as.Date("2019-01-01"))
      
indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
   column_spec(2, T, color = "red" ) 

date	value
2019-01-01	76.74
2019-02-01	76.28
2019-03-01	76.16
2019-04-01	75.41
2019-05-01	75.39
2019-06-01	75.72
2019-07-01	75.32
2019-08-01	75.69
2019-09-01	75.11
2019-10-01	74.60
2019-11-01	75.20
2019-12-01	75.25
2020-01-01	75.19
2020-02-01	75.16
2020-03-01	71.42
2020-04-01	60.03
2020-05-01	62.30
2020-06-01	66.91
2020-07-01	69.19

indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = "Capacity Utilization: Manufacturing", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Percent of Capacity",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Capacity Utilization : Total Industry (TCU) Monthly. Percent Capacity

symbol <-fredr_series_observations(series_id = "TCU", 
      observation_start = as.Date("2019-01-01"))
      
indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
   column_spec(2, T, color = "red" ) 

date	value
2019-01-01	79.00
2019-02-01	78.46
2019-03-01	78.40
2019-04-01	77.76
2019-05-01	77.80
2019-06-01	77.69
2019-07-01	77.42
2019-08-01	77.84
2019-09-01	77.43
2019-10-01	76.99
2019-11-01	77.57
2019-12-01	77.17
2020-01-01	76.88
2020-02-01	76.93
2020-03-01	73.61
2020-04-01	64.20
2020-05-01	64.78
2020-06-01	68.46
2020-07-01	70.56

indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = "Capacity Utilization Index: Total Industry (TCU)", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Monthly", y="percent",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Industrial Production: Manufacturing (NAICS) (IPGMFN) Index 2012=100, Monthly

symbol <-fredr_series_observations(series_id = "IPGMFN", 
      observation_start = as.Date("2019-01-01"))
      
indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
   column_spec(2, T, color = "red" ) 

date	value
2019-01-01	104.33
2019-02-01	105.52
2019-03-01	106.91
2019-04-01	105.68
2019-05-01	105.70
2019-06-01	108.15
2019-07-01	103.77
2019-08-01	107.68
2019-09-01	106.66
2019-10-01	106.30
2019-11-01	105.77
2019-12-01	104.51
2020-01-01	103.60
2020-02-01	105.47
2020-03-01	101.32
2020-04-01	84.06
2020-05-01	88.19
2020-06-01	96.34
2020-07-01	95.74

indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = "Industrial Production: Manufacturing (NAICS)", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Index 2012=100",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Capacity Utilization: Manufacturing (NAICS) (MCUMFN) Monthly. Percent Capacity

symbol <-fredr_series_observations(series_id = "MCUMFN", 
      observation_start = as.Date("2019-01-01"))
      
indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
   column_spec(2, T, color = "red" ) 

date	value
2019-01-01	77.24
2019-02-01	76.75
2019-03-01	76.64
2019-04-01	75.88
2019-05-01	75.88
2019-06-01	76.22
2019-07-01	75.83
2019-08-01	76.21
2019-09-01	75.62
2019-10-01	75.10
2019-11-01	75.76
2019-12-01	75.84
2020-01-01	75.74
2020-02-01	75.66
2020-03-01	71.91
2020-04-01	60.37
2020-05-01	62.72
2020-06-01	67.45
2020-07-01	69.77

indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = "Capacity Utilization: Manufacturing (NAICS)", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Monthly", y="Percent Capacity",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Industrial Production : Crude oil (IPG211111CN) Index 2012=100, monthly

symbol <-fredr_series_observations(series_id = "IPG211111CN", 
      observation_start = as.Date("2019-01-01"))
      
indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
   column_spec(2, T, color = "red" ) 

date	value
2019-01-01	182.6
2019-02-01	178.5
2019-03-01	181.9
2019-04-01	185.4
2019-05-01	185.3
2019-06-01	184.5
2019-07-01	180.9
2019-08-01	189.5
2019-09-01	190.9
2019-10-01	193.9
2019-11-01	196.8
2019-12-01	196.0
2020-01-01	195.2
2020-02-01	195.0
2020-03-01	194.9
2020-04-01	183.5
2020-05-01	153.1
2020-06-01	153.0
2020-07-01	155.0

indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = " Crude oil Production", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Monthly", y="Index 2012 = 100",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Industrial Production: Durable manufacturing: Motor vehicles and parts (IPG3361T3N) Index 2012=100, monthly

symbol <-fredr_series_observations(series_id = "IPG3361T3N", 
      observation_start = as.Date("2019-01-01"))
      
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
14	2020-02-01	139.29
15	2020-03-01	100.47
16	2020-04-01	22.34
17	2020-05-01	46.58
18	2020-06-01	106.74
19	2020-07-01	106.33

indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = "Motor vehicles and parts Production", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Index 2012=100",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Industrial Production: Consumer goods (IPB51000N) Index 2012=100, monthly

symbol <-fredr_series_observations(series_id = "IPB51000N", 
      observation_start = as.Date("2019-01-01"))
      
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
14	2020-02-01	107.57
15	2020-03-01	101.03
16	2020-04-01	83.83
17	2020-05-01	87.31
18	2020-06-01	98.59
19	2020-07-01	101.13

indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = "Consumer goods Production", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y=" Index 2012=100",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Industrial Production: Nondurable manufacturing: Food, beverage, and tobacco (IPG311A2N) Index 2012=100, monthly

symbol <-fredr_series_observations(series_id = "IPG311A2N", 
      observation_start = as.Date("2019-01-01"))
      
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
14	2020-02-01	110.13
15	2020-03-01	109.29
16	2020-04-01	98.29
17	2020-05-01	100.90
18	2020-06-01	108.14
19	2020-07-01	106.05

indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = "Production of Food, Beverage, and Tobacco", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y=" Index 2012=100",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Industrial Production: Durable manufacturing: Aerospace and miscellaneous transportation equipment (IPG3364T9N) Index 2012=100, monthly

symbol <-fredr_series_observations(series_id = "IPG3364T9N", 
      observation_start = as.Date("2019-01-01"))
      
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
14	2020-02-01	91.10
15	2020-03-01	86.75
16	2020-04-01	65.23
17	2020-05-01	72.97
18	2020-06-01	75.35
19	2020-07-01	78.82

indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = " Industrial Production: Aerospace and miscellaneous transportation equipment", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y=" Index 2012=100",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Capacity Utilization: Durable Manufacturing: Automobile and light duty motor vehicle (CAPUTLG33611S) Percent of Capacity, monthly

symbol <-fredr_series_observations(series_id = "CAPUTLG33611S", 
      observation_start = as.Date("2019-01-01"))
      
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
14	2020-02-01	85.1555
15	2020-03-01	52.4922
16	2020-04-01	0.7261
17	2020-05-01	17.2452
18	2020-06-01	62.2646
19	2020-07-01	91.9485

indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = " Capacity Utilization: Automobile and light duty motor vehicle", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y=" Index 2012=100",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()