Skip to contents

This function will take in a value column and return any number n moving averages.

Usage

ts_sma_plot(
  .data,
  .date_col,
  .value_col,
  .sma_order = 2,
  .func = mean,
  .align = "center",
  .partial = FALSE
)

Arguments

.data

The data that you are passing, must be a data.frame/tibble.

.date_col

The column that holds the date.

.value_col

The column that holds the value.

.sma_order

This will default to 1. This can be a vector like c(2,4,6,12)

.func

The unquoted function you want to pass, mean, median, etc

.align

This can be either "left", "center", "right"

.partial

This is a bool value of TRUE/FALSE, the default is TRUE

Value

Will return a list object.

Details

This function will accept a time series object or a tibble/data.frame. This is a simple wrapper around timetk::slidify_vec(). It uses that function to do the underlying moving average work.

It can only handle a single moving average at a time and therefore if multiple are called for, it will loop through and append data to a tibble object.

Author

Steven P. Sanderson II, MPH

Examples

df <- ts_to_tbl(AirPassengers)
out <- ts_sma_plot(df, date_col, value, .sma_order = c(3,6))

out$data
#> # A tibble: 288 × 5
#>    index     date_col   value sma_order sma_value
#>    <yearmon> <date>     <dbl> <fct>         <dbl>
#>  1 Jan 1949  1949-01-01   112 3               NA 
#>  2 Feb 1949  1949-02-01   118 3              121.
#>  3 Mar 1949  1949-03-01   132 3              126.
#>  4 Apr 1949  1949-04-01   129 3              127.
#>  5 May 1949  1949-05-01   121 3              128.
#>  6 Jun 1949  1949-06-01   135 3              135.
#>  7 Jul 1949  1949-07-01   148 3              144.
#>  8 Aug 1949  1949-08-01   148 3              144 
#>  9 Sep 1949  1949-09-01   136 3              134.
#> 10 Oct 1949  1949-10-01   119 3              120.
#> # … with 278 more rows
#> # ℹ Use `print(n = ...)` to see more rows

out$plots$static_plot
#> Warning: Removed 7 row(s) containing missing values (geom_path).