ts_ma_plot | R Documentation |
This function will produce two plots. Both of these are moving average plots.
One of the plots is from xts::plot.xts()
and the other a ggplot2
plot. This
is done so that the user can choose which type is best for them. The plots are
stacked so each graph is on top of the other.
ts_ma_plot(
.data,
.date_col,
.value_col,
.ts_frequency = "monthly",
.main_title = NULL,
.secondary_title = NULL,
.tertiary_title = NULL
)
.data |
The data you want to visualize. This should be pre-processed and
the aggregation should match the |
.date_col |
The data column from the |
.value_col |
The value column from the |
.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. |
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.
A few time series data sets and two plots.
Steven P. Sanderson II, MPH
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
)
output$pgrid
output$xts_plt
output$data_summary_tbl %>% head()
output <- ts_ma_plot(
.data = data_tbl,
.date_col = date_col,
.value_col = value,
.ts_frequency = "week"
)
output$pgrid
output$xts_plt
output$data_summary_tbl %>% head()
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