Nothing
## ----setup, include = FALSE----------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
library(valetr)
## ----eval=TRUE, echo=TRUE, warning=FALSE, message=FALSE------------------
cpis <- getSeriesData(series=c("V41690973","V41693242"), recent_years=21L) # get data
# load data.table
library(data.table)
# calcule the CPI %
cpis <- lapply(cpis, function(x){
# change last col name to cpi
names(x)[length(x)] <- "value"
x[["value"]] <- as.numeric(x[["value"]]) # cpi val as numeric
x[["d"]] <- format(as.Date(x[["d"]]), "%Y-%m") # format date
data.table::setDT(x)
# calculate % change over the past 12 mo
x[, chng := value/data.table::shift(value, n = 12) - 1]
# remove NAs (due to lag)
x <- x[!is.na(chng), ]
return(x)
})
# bind datasets
cpis <- do.call(rbind, cpis)
head(cpis)
## ----eval=TRUE, echo=TRUE, warning=FALSE, message=FALSE------------------
# compare series
library(ggplot2)
ggplot(cpis,
aes(y=chng, x=d, group=series_label, colour=series_label)
) +
geom_line() +
labs(x=NULL,
y = "% change over the past 12 months",
title="Core CPI series appears less\nvolatile than Total CPI",
caption=paste0("Valet API series: ",
paste0(unique(cpis[["series_name"]]),collapse =","))) +
scale_y_continuous(labels=function(x) paste0(round(x*100, 2), "%")) +
theme_minimal() +
theme(axis.text.x = element_blank(),
panel.grid = element_blank(),
legend.title = element_blank(),
legend.position = c(.8,.85))
## ----eval=TRUE, echo=TRUE, warning=FALSE, message=FALSE------------------
# capture m aggregates
series <- regexSeriesLabel(pattern="(?i)m\\d\\+{1,} \\(gross\\)")
## ----eval=TRUE, echo=FALSE, warning=FALSE, message=FALSE-----------------
# capture m aggregates
series
## ----eval=TRUE, echo=TRUE, message=FALSE, warning=FALSE------------------
fxsInfo <- getSeriesInfo(patternGroupLabel = "exchange rate",
ignore.case=TRUE)
## ----eval=TRUE, echo=TRUE, message=FALSE,warning=FALSE-------------------
head(fxsInfo)
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