adjustForInflation.R

# Reference: https://www.bls.gov/developers/api_r.htm
library(magrittr)
library(dplyr)
library(devtools)
install_github("mikeasilva/blsAPI")  # https://github.com/mikeasilva/blsAPI
library(rjson)
library(blsAPI)

payload <- list("seriesid" = c("CUUR0000SA0L1E"),
                "startyear" = 2016,
                "endyear" = 2021,
                "annualaverage" = TRUE)
# payload <- list("seriesid" = c("CUUR0000SA0L1E"),
#                 "startyear" = 2016,
#                 "endyear" = 2021,
#                 "annualaverage" = TRUE,
#                 "registrationkey" = <BLS Public Data API Signature (Version 2.0)>)
response <- blsAPI(payload, 2) 
json <- fromJSON(response) 
df <- data.frame(year = character(),
                 period = character(), 
                 periodName = character(),
                 value = character(),
                 stringsAsFactors = FALSE)
i <- 0
for (d in json$Results$series[[1]]$data) {
  i <- i + 1
  df[i, ] <- unlist(d)
}

df
df %>%
  filter(periodName == "Annual") %>%
  mutate(value = as.numeric(value)) %>%
  mutate(inflationFactor = max(value) / value)
df %>%
  filter(periodName != "Annual") %>%
  mutate(value = as.numeric(value)) %>%
  group_by(year) %>%
  summarize(dataPoints = n(),
            avgCalculated = mean(value)) %>%
  ungroup() %>%
  inner_join(df %>% filter(periodName == "Annual"))