Total Assets, All Commercial Banks (TLAACBM027NBOG)

symbol <-fredr_series_observations(series_id = "TLAACBM027NBOG", 
      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 17025
2019-02-01 17041
2019-03-01 17108
2019-04-01 17117
2019-05-01 17179
2019-06-01 17329
2019-07-01 17341
2019-08-01 17504
2019-09-01 17498
2019-10-01 17585
2019-11-01 17747
2019-12-01 17860
2020-01-01 17858
2020-02-01 17962
2020-03-01 18938
2020-04-01 20026
2020-05-01 20295
2020-06-01 20186
2020-07-01 20017 
indicator <-as.data.frame(symbol)[,c(1,3)]

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

Total Liabilities, All Commercial Banks (TLBACBW027NBOG)

symbol <-fredr_series_observations(series_id = "TLBACBW027NBOG", 
      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
2019-01-02 15204
2019-01-09 15208
2019-01-16 15141
2019-01-23 15073
2019-01-30 15079
2019-02-06 15111
2019-02-13 15153
2019-02-20 15090
2019-02-27 15161
2019-03-06 15184
2019-03-13 15182
2019-03-20 15150
2019-03-27 15183
2019-04-03 15241
2019-04-10 15245
2019-04-17 15168
2019-04-24 15144
2019-05-01 15175
2019-05-08 15230
2019-05-15 15296
2019-05-22 15165
2019-05-29 15242
2019-06-05 15358
2019-06-12 15424
2019-06-19 15336
2019-06-26 15342
2019-07-03 15408
2019-07-10 15378
2019-07-17 15356
2019-07-24 15345
2019-07-31 15403
2019-08-07 15566
2019-08-14 15532
2019-08-21 15458
2019-08-28 15497
2019-09-04 15556
2019-09-11 15537
2019-09-18 15445
2019-09-25 15476
2019-10-02 15596
2019-10-09 15649
2019-10-16 15642
2019-10-23 15555
2019-10-30 15605
2019-11-06 15729
2019-11-13 15785
2019-11-20 15736
2019-11-27 15815
2019-12-04 15854
2019-12-11 15944
2019-12-18 15912
2019-12-25 15865
2020-01-01 15794
2020-01-08 15913
2020-01-15 15930
2020-01-22 15777
2020-01-29 15850
2020-02-05 15883
2020-02-12 15876
2020-02-19 15953
2020-02-26 15953
2020-03-04 16206
2020-03-11 16339
2020-03-18 16744
2020-03-25 17385
2020-04-01 17662
2020-04-08 17701
2020-04-15 18009
2020-04-22 18078
2020-04-29 18242
2020-05-06 18277
2020-05-13 18323
2020-05-20 18241
2020-05-27 18260
2020-06-03 18248
2020-06-10 18274
2020-06-17 18172
2020-06-24 18037
2020-07-01 18083
2020-07-08 18085
2020-07-15 18030
2020-07-22 17884
2020-07-29 17936
2020-08-05 18001 
indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = "Total Liabilities, All Commercial Banks", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Monthly", y="Billions of Dollars",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Deposits, All Commercial Banks (DPSACBW027NBOG)

symbol <-fredr_series_observations(series_id = "DPSACBW027NBOG", 
      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
79 2020-07-01 15613
80 2020-07-08 15626
81 2020-07-15 15619
82 2020-07-22 15407
83 2020-07-29 15439
84 2020-08-05 15533 
indicator <-as.data.frame(symbol)[,c(1,3)]

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

Allowance for Loan and Lease Losses, All Commercial Banks (ALLACBM027NBOG)

symbol <-fredr_series_observations(series_id = "ALLACBM027NBOG", 
      observation_start = as.Date("2010-01-01"))
      
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
122 2020-02-01 113.5
123 2020-03-01 116.0
124 2020-04-01 142.1
125 2020-05-01 147.3
126 2020-06-01 155.6
127 2020-07-01 185.1 
indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = "Allowance for Loan and Lease Losses _All Commercial Banks", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Monthly", y="Billions of Dollars",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Consumer Loans: Credit Cards and Other Revolving Plans, All Commercial Banks (CCLACBM027NBOG)

symbol <-fredr_series_observations(series_id = "CCLACBM027NBOG", 
      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
2019-01-01 825.3
2019-02-01 812.5
2019-03-01 799.0
2019-04-01 805.2
2019-05-01 811.3
2019-06-01 819.9
2019-07-01 821.8
2019-08-01 829.7
2019-09-01 831.1
2019-10-01 835.6
2019-11-01 845.5
2019-12-01 873.1
2020-01-01 863.5
2020-02-01 850.1
2020-03-01 833.5
2020-04-01 786.2
2020-05-01 761.1
2020-06-01 758.8
2020-07-01 757.7 
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 Loans: Credit Cards and Other Revolving Plans\nAll Commerical Banks", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Monthly", y="Billions of Dollars",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Real Estate Loans, All Commercial Banks (RELACBW027SBOG)

symbol <-fredr_series_observations(series_id = "RELACBW027SBOG", 
      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
79 2020-07-01 4690
80 2020-07-08 4701
81 2020-07-15 4698
82 2020-07-22 4702
83 2020-07-29 4695
84 2020-08-05 4696 
indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = "Real Estate Loans, All Commercial Banks", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Billions of Dollars",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Commercial Real Estate Loans: Construction and Land Development Loans, All Commercial Banks (CLDACBW027NBOG)

symbol <-fredr_series_observations(series_id = "CLDACBW027NBOG", 
      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
79 2020-07-01 369.9
80 2020-07-08 369.8
81 2020-07-15 371.2
82 2020-07-22 371.9
83 2020-07-29 373.0
84 2020-08-05 372.7 
indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = "Real Estate Construction and Land Development Loans _All Commercial Banks", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Billions of Dollars",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Revolving Home Equity Loans, All Commercial Banks (RHEACBW027NBOG)

symbol <-fredr_series_observations(series_id = "RHEACBW027NBOG", 
      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
79 2020-07-01 304.5
80 2020-07-08 303.6
81 2020-07-15 303.4
82 2020-07-22 302.5
83 2020-07-29 301.4
84 2020-08-05 299.7 
indicator <-as.data.frame(symbol)[,c(1,3)]

indicator %>% ggplot() + 
  geom_line(mapping = aes(x=date,y=value),color="red",size=1)  +
     labs(title = "Real Estate Revolving Home Equity Loans, All Commercial Banks", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
       x="Time", y="Billions of Dollars",
       caption = "Data source: FRED Federal Reserve.   Illustration by @JoeLongSanDiego")+
    theme_economist()

Commercial Paper Outstanding (COMPOUT)

symbol <-fredr_series_observations(series_id = "COMPOUT", 
      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
81 2020-07-15 1026
82 2020-07-22 1021
83 2020-07-29 1019
84 2020-08-05 1018
85 2020-08-12 1010
86 2020-08-19 1007 
indicator <-as.data.frame(symbol)[,c(1,3)]

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