README.md

In Reckziegel/astimeseries: Correctly coerce R objects to a timeSeries class

astimeseries

The objective of astimeseries is to simplify and assure the correct coercion among data structures used in the tidyverse to R-Mertrics (timeSeries class).

Installation

You can install the development version from GitHub with:

install.packages("devtools")
devtools::install_github("Reckziegel/astimeseries")

Example

Suppose you have the following tibble:

library(tibble)

tbl <- tibble(date = as.Date(c('2019-01-01', '2019-01-02', '2019-01-03')),
               a    = rnorm(3),
               b    = rnorm(3),
               c    = rnorm(3))

tbl
#> # A tibble: 3 x 4
#>   date            a      b      c
#>   <date>      <dbl>  <dbl>  <dbl>
#> 1 2019-01-01 -0.848  0.371 -0.476
#> 2 2019-01-02  0.226  0.435 -1.25 
#> 3 2019-01-03  1.37  -1.29  -1.18

If you try to coerce the tbl object to a timeSeries (the data structure R-Metrics likes to work with), the timestamps attributes are lost:

library(timeSeries)
#> Loading required package: timeDate

as.timeSeries(tbl)
#> 
#>               a          b          c
#> [1,] -0.8484120  0.3709798 -0.4759263
#> [2,]  0.2262966  0.4348504 -1.2538615
#> [3,]  1.3694029 -1.2940927 -1.1763620

Instead, it’s safer to use as_timeseries to ensure all information is keeped approprietly.

# library(astimeseries)
as_timeseries(tbl)
#> GMT
#>                     a          b          c
#> 2019-01-01 -0.8484120  0.3709798 -0.4759263
#> 2019-01-02  0.2262966  0.4348504 -1.2538615
#> 2019-01-03  1.3694029 -1.2940927 -1.1763620

Reckziegel/astimeseries documentation built on Nov. 13, 2019, 12:32 a.m.