Plot the output of the following nixtla_client functions: forecast, historic, anomaly_detection, and cross_validation.

Usage

nixtla_client_plot(
  df,
  fcst = NULL,
  h = NULL,
  id_col = "unique_id",
  time_col = "ds",
  target_col = "y",
  unique_ids = NULL,
  max_insample_length = NULL,
  plot_anomalies = FALSE
)

Arguments

df: A tsibble or a data frame with time series data (insample values).
fcst: A tsibble or a data frame with the 'TimeGPT' point forecast and the prediction intervals (if available).
h: Forecast horizon.
id_col: Column that identifies each series.
time_col: Column that identifies each timestep.
target_col: Column that contains the target variable.
unique_ids: Time series to plot. If NULL (default), selection will be random.
max_insample_length: Max number of insample observations to be plotted.
plot_anomalies: Whether or not to plot anomalies.

Value

Plot with historical data and 'TimeGPT”s output (if available).

Examples

if (FALSE) { # \dontrun{
  nixtlar::nixtla_set_api_key("YOUR_API_KEY")
  df <- nixtlar::electricity
  fcst <- nixtlar::nixtla_client_forecast(df, h=8, id_col="unique_id", level=c(80,95))
  nixtlar::timegpt_plot(df, fcst, h=8, id_col="unique_id")
} # }