Visualize time series interactively

Generates an interactive plotly time series plot from a data frame, optionally overlaying phenological events.

Usage

visualize_time_series(
  df_ts,
  df_doy = NULL,
  var = "value",
  ylab = "Value",
  smooth = FALSE,
  lambda = 50,
  facet_var = NULL,
  color_palette = "viridis"
)

Arguments

df_ts

Data frame. Must contain either a time (POSIX) or date (Date) column, an id column, and the variable to plot.

df_doy

Optional data frame. Time of phenological events with columns year and doy. Default: NULL.

var

Character. Name of the column in df_ts to plot (default: "value").

ylab

Character. Label for the y-axis (default: "Value").

smooth

Logical. If TRUE, applies gap-filling and smoothing to data points with Whittaker smoothing (default: FALSE).

lambda

Numeric. Smoothing parameter for Whittaker smoothing (default: 50).

facet_var

Character or NULL. Column name in df_ts and df_doy to facet by (e.g., "site" or "id").

color_palette

Character. Name of a viridis palette for line colors (default: "viridis").

Value

An interactive plotly object when supported, a static ggplot object otherwise.

Examples

if (FALSE) { # \dontrun{
# Example: Visualize a time series with phenological events
visualize_time_series(
  df_ts = df_ts,
  df_doy = df_doy,
  var = "value",
  ylab = "Value",
  smooth = TRUE,
  lambda = 50,
  facet_var = "id",
  color_palette = "viridis"
)
} # }