Time Series Plot

This is a warpper function to the timetk::plot_time_series() function with a limited functionality parameter set. To see the full reference please visit the timetk package site.

Usage

ts_plt(
  .data,
  .date_col,
  .value_col,
  .color_col = NULL,
  .facet_col = NULL,
  .facet_ncol = NULL,
  .interactive = FALSE
)

Arguments

.data

The data to pass to the function, must be a tibble/data.frame.

.date_col

The column holding the date.

.value_col

The column holding the value.

.color_col

The column holding the variable for color.

.facet_col

The column holding the variable for faceting.

.facet_ncol

How many columns do you want.

.interactive

Return a plotly plot if set to TRUE and a static ggplot2 plot if set to FALSE. The default is FALSE.

Value

A plotly plot or a ggplot2 static plot

Details

This function takes only a few of the arguments in the function and presets others while choosing the defaults on others. The smoother functionality is turned off.

See also

https://business-science.github.io/timetk/reference/plot_time_series.html

Other Plotting Functions: diverging_bar_plt(), diverging_lollipop_plt(), gartner_magic_chart_plt(), los_ra_index_plt(), ts_alos_plt(), ts_median_excess_plt(), ts_readmit_rate_plt()

Author

Steven P. Sanderson II, MPH

Examples

suppressPackageStartupMessages(library(dplyr))
library(timetk)
library(healthyR.data)

healthyR.data::healthyR_data %>%
  filter(ip_op_flag == "I") %>%
  select(visit_end_date_time, service_line) %>%
  filter_by_time(
    .date_var = visit_end_date_time
    , .start_date = "2020"
    ) %>%
  group_by(service_line) %>%
  summarize_by_time(
    .date_var = visit_end_date_time
    , .by = "month"
    , visits = n()
  ) %>%
 ungroup() %>%
 ts_plt(
   .date_col = visit_end_date_time
   , .value_col = visits
   , .color_col = service_line
 )