Inflation Trends _ indexing to January 2019

1-Month Real Interest Rate (REAINTRATREARAT1MO)

series_ls <-fredr_series_observations(series_id = "REAINTRATREARAT1MO",observation_start = as.Date("2019-01-01")) 
# convert series list to dataframe
series_df <- do.call(cbind.data.frame, series_ls)

# plotting data
ggplot(series_df) + geom_line(mapping = aes(x=date,y=value),  color = "blue") + geom_hline(yintercept=0,color="red") +
   
  labs(x = "Monthly",y = "Percent, \nNot Seasonally Adjusted",
      title = "1-Month Real Interest Rate (REAINTRATREARAT1MO) ", 
      caption = "Source: U.S. Bureau of Labor Statistics and Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("Monthly from {min(series_ls$date)} through {max(series_ls$date)}"))+
      theme_economist()

Consumer Price Index for All Urban Consumers: All Items (CPIAUCSL)

series_ls <-fredr_series_observations(series_id = "CPIAUCSL",observation_start = as.Date("2019-01-01")) 
# convert series list to dataframe
series_df <- do.call(cbind.data.frame, series_ls)
series_df$change <- series_df$value -  series_df$value[[1]]

# plotting data
ggplot(series_df) + geom_line(mapping = aes(x=date,y=value),  color = "blue") +
   geom_rect(aes(xmin= dmy('01-01-2021'), xmax=xdate, ymin = -Inf, ymax = Inf),
                   fill = "white", alpha = 0.02)+
  labs(x = "Monthly",y = "Index 1982-1984=100\nSeasonally Adjusted",
      title = "Consumer Price Index for All Urban Consumers", 
      caption = "Source: U.S. Bureau of Labor Statistics and Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("Monthly from {min(series_ls$date)} through {max(series_ls$date)}"))+
      theme_economist()

ggplot(series_df) + geom_line(mapping = aes(x=date,y=change),  color = "blue") +
   geom_rect(aes(xmin= dmy('01-01-2021'), xmax=xdate, ymin = -Inf, ymax = Inf),
                   fill = "white", alpha = 0.02)+
  labs(x = "Monthly",y = "Base Index Jan/2019\nSeasonally Adjusted",
      title = "Consumer Price Index for All Urban Consumers _ indexing from January 2019", 
      caption = "Source: U.S. Bureau of Labor Statistics and Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("Monthly from {min(series_ls$date)} through {max(series_ls$date)}"))+
      theme_economist()

Consumer Price Index for All Urban Consumers: Food and Beverages (CPIFABSL)

series_ls <-fredr_series_observations(series_id = "CPIFABSL",observation_start = as.Date("2019-01-01")) 
# convert series list to dataframe
series_df <- do.call(cbind.data.frame, series_ls)
series_df$change <- series_df$value -  series_df$value[[1]]

# plotting data
ggplot(series_df) + geom_line(mapping = aes(x=date,y=value),  color = "blue") +
   geom_rect(aes(xmin= dmy('01-01-2021'), xmax=xdate, ymin = -Inf, ymax = Inf),
                   fill = "white", alpha = 0.02)+
  labs(x = "Monthly",y = "Index 1982-1984=100\nSeasonally Adjusted",
      title = "Food and Beverages: Consumer Price Index ", 
      caption = "Source: U.S. Bureau of Labor Statistics and Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("Monthly from {min(series_ls$date)} through {max(series_ls$date)}"))+
      theme_economist()

ggplot(series_df) + geom_line(mapping = aes(x=date,y=change),  color = "blue") +
   geom_rect(aes(xmin= dmy('01-01-2021'), xmax=xdate, ymin = -Inf, ymax = Inf),
                   fill = "white", alpha = 0.02)+
  labs(x = "Monthly",y = "Base Index Jan/2019\nSeasonally Adjusted",
      title = "Food and Beverages: Consumer Price Index _ indexing from January 2019", 
      caption = "Source: U.S. Bureau of Labor Statistics and Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("Monthly from {min(series_ls$date)} through {max(series_ls$date)}"))+
      theme_economist()

Consumer Price Index for All Urban Consumers: Energy in U.S. City Average (CPIENGNS)

series_ls <-fredr_series_observations(series_id = "CPIENGNS",observation_start = as.Date("2019-01-01")) 
# convert series list to dataframe
series_df <- do.call(cbind.data.frame, series_ls)
series_df$change <- series_df$value -  series_df$value[[1]]

# plotting data
ggplot(series_df) + geom_line(mapping = aes(x=date,y=value),  color = "blue") +
   geom_rect(aes(xmin= dmy('01-01-2021'), xmax=xdate, ymin = -Inf, ymax = Inf),
                   fill = "white", alpha = 0.02)+
  labs(x = "Monthly",y = "Index 1982-1984=100\nNot Seasonally Adjusted",
      title = "Energy: Consumer Price Index ", 
      caption = "Source: U.S. Bureau of Labor Statistics and Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("Monthly from {min(series_ls$date)} through {max(series_ls$date)}"))+
      theme_economist()

ggplot(series_df) + geom_line(mapping = aes(x=date,y=change),  color = "blue") +
   geom_rect(aes(xmin= dmy('01-01-2021'), xmax=xdate, ymin = -Inf, ymax = Inf),
                   fill = "white", alpha = 0.02)+
  labs(x = "Monthly",y = "Base Index Jan/2019\nSeasonally Adjusted",
      title = "Energy: Consumer Price Index _ indexing from January 2019", 
      caption = "Source: U.S. Bureau of Labor Statistics and Federal Reserve Bank of St. Louis\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("Monthly from {min(series_ls$date)} through {max(series_ls$date)}"))+
      theme_economist()