Time Series Moving Average Plot — ts_ma

This function will produce a ggplot2 plot with facet wrapping. The plot contains three moving average panels stacked on top of each other using facet_wrap. The panels show the main time series with moving average, and two difference calculations: Diff A shows sequential period-over-period percentage changes (e.g., month-over-month or week-over-week), and Diff B shows year-over-year percentage changes.

Usage

ts_ma_plot(
  .data,
  .date_col,
  .value_col,
  .ts_frequency = "monthly",
  .main_title = NULL,
  .secondary_title = NULL,
  .tertiary_title = NULL
)

Arguments

.data: The data you want to visualize. This should be pre-processed and the aggregation should match the .frequency argument.
.date_col: The data column from the .data argument.
.value_col: The value column from the .data argument
.ts_frequency: The frequency of the aggregation, quoted, ie. "monthly", anything else will default to weekly, so it is very important that the data passed to this function be in either a weekly or monthly aggregation.
.main_title: The title of the main plot.
.secondary_title: The title of the second plot.
.tertiary_title: The title of the third plot.

Value

A list containing the ggplot2 plot object and the summary data table.

Details

This function expects to take in a data.frame/tibble. It will return a list object so it is a good idea to save the output to a variable and extract from there.

Author

Steven P. Sanderson II, MPH

Examples

suppressPackageStartupMessages(library(dplyr))

data_tbl <- ts_to_tbl(AirPassengers) %>%
  select(-index)

output <- ts_ma_plot(
  .data = data_tbl,
  .date_col = date_col,
  .value_col = value
)
#> Warning: Removed 11 rows containing missing values or values outside the scale range
#> (`geom_line()`).

output$pgrid

output$data_summary_tbl %>% tail()
#> # A tibble: 6 × 5
#>   date_col   value  ma12 diff_a diff_b
#>   <date>     <dbl> <dbl>  <dbl>  <dbl>
#> 1 1960-07-01   622  459.  16.3   13.5 
#> 2 1960-08-01   606  463.  -2.57   8.41
#> 3 1960-09-01   508  467. -16.2    9.72
#> 4 1960-10-01   461  472.  -9.25  13.3 
#> 5 1960-11-01   390  474. -15.4    7.73
#> 6 1960-12-01   432  476.  10.8    6.67

output <- ts_ma_plot(
  .data = data_tbl,
  .date_col = date_col,
  .value_col = value,
  .ts_frequency = "month"
)
#> Warning: Removed 51 rows containing missing values or values outside the scale range
#> (`geom_line()`).

output$pgrid

output$data_summary_tbl %>% tail()
#> # A tibble: 6 × 5
#>   date_col   value  ma12 diff_a diff_b
#>   <date>     <dbl> <dbl>  <dbl>  <dbl>
#> 1 1960-07-01   622  394.  16.3   96.2 
#> 2 1960-08-01   606  400.  -2.57  93.6 
#> 3 1960-09-01   508  404. -16.2   59.7 
#> 4 1960-10-01   461  405.  -9.25  23.3 
#> 5 1960-11-01   390  405. -15.4   -5.57
#> 6 1960-12-01   432  405.  10.8    6.67