In kvasilopoulos/transx: Transform Univariate Time Series

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

The problem arises when we have to use time-series in a data.frame or use time-series operations like lag and diff for numeric vectors in a data.frame. Let's look into an example.

library(transx)

First, wee restrict tibble printing options to minimize the space occupied.

library(dplyr)
options(tibble.print_min = 3)

Let's load the economics dataset from ggplot2 for illustration.

econ <- ggplot2::economics
econ

Then, we are going to use some stats functions:

mutate(econ, pop_lag = stats::lag(as.ts(pop)))

base::lag only works on ts objects. However, dplyr has thought about this problem

mutate(econ, pop_lag = dplyr::lag(pop))

However, this problem extends to all the univariate functions that are applied in the same manner in a data.frame. For example

mutate(econ, pop_diff = base::diff(pop))

The idea for transx is coming from the need to construct wrapper functions.

diffx <- function(x, ...) x - dplyr::lag(x, ... )

mutate(econ, pop_diff = diffx(pop))

kvasilopoulos/transx documentation built on Jan. 26, 2021, 6:14 p.m.