gravitas (version 0.1.2)

prob_plot: Plotting probability distributions across granularities

Description

Plot probability distribution of univariate series across bivariate temporal granularities.

Usage

prob_plot(
  .data,
  gran1 = NULL,
  gran2 = NULL,
  hierarchy_tbl = NULL,
  response = NULL,
  plot_type = NULL,
  quantile_prob = c(0.01, 0.1, 0.25, 0.5, 0.75, 0.9, 0.99),
  facet_h = NULL,
  symmetric = TRUE,
  alpha = 0.8,
  ...
)

Arguments

.data

a tsibble

gran1

the granularity which is to be placed across facets. Can be column names if required granularity already exists in the tsibble. For example, a column with public holidays which needs to be treated as granularity, can be included here.

gran2

the granularity to be placed across x-axis. Can be column names if required granularity already exists in the tsibble.

hierarchy_tbl

A hierarchy table specifying the hierarchy of units and their relationships.

response

response variable to be plotted.

plot_type

type of distribution plot. Options include "boxplot", "lv" (letter-value), "quantile", "ridge" or "violin".

quantile_prob

numeric vector of probabilities with value in [0,1] whose sample quantiles are wanted. Default is set to "decile" plot.

facet_h

levels of facet variable for which facetting is allowed while plotting bivariate temporal granularities.

symmetric

If TRUE, symmetic quantile area plot is drawn. If FALSE, only quantile lines are drawn instead of area. If TRUE, length of quantile_prob should be odd and ideally the quantile_prob should be a symmetric vector with median at the middle position.

alpha

level of transperancy for the quantile area

...

other arguments to be passed for customising the obtained ggplot object.

Value

a ggplot object which can be customised as usual.

Examples

# NOT RUN {
library(tsibbledata)
library(ggplot2)
library(tsibble)
library(lvplot)
library(dplyr)

vic_elec %>% prob_plot(
  gran1 = "hour_day", gran2 = "day_week",
  response = "Demand", plot_type = "quantile",
  quantile_prob = c(0.1, 0.25, 0.5, 0.75, 0.9),
  symmetric = TRUE, outlier.colour = "red",
  outlier.shape = 2, palette = "Dark2"
)

cricket_tsibble <- cricket %>%
  mutate(data_index = row_number()) %>%
  as_tsibble(index = data_index)

hierarchy_model <- tibble::tibble(
  units = c("index", "over", "inning", "match"),
  convert_fct = c(1, 20, 2, 1)
)

cricket_tsibble %>%
  prob_plot("inning", "over",
    hierarchy_tbl = hierarchy_model,
    response = "runs_per_over",
    plot_type = "lv"
  )
# }

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