Description Usage Arguments Value Examples
Recommendations on plot choices, interaction, number of observations and intra or inter facet homogeneity. Important summaries before drawing distribution plots.
1  | gran_advice(.data, gran1, gran2, hierarchy_tbl = NULL, ...)
 | 
.data | 
 a tsibble.  | 
gran1, gran2 | 
 granularities.  | 
hierarchy_tbl | 
 A hierarchy table specifying the hierarchy of units and their relationships.  | 
... | 
 other arguments to be passed for appropriate labels.  | 
Summary check points before visualizing distribution across bivariate granularities
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19  | library(dplyr)
library(ggplot2)
smart_meter10 %>%
filter(customer_id == "10017936") %>%
  gran_advice(gran1 = "wknd_wday",
            gran2 = "hour_day")
# choosing quantile plots from plot choices
smart_meter10 %>%
filter(customer_id == "10017936") %>%
  prob_plot(
    gran1 = "wknd_wday",
    gran2 = "hour_day",
    response = "general_supply_kwh",
    plot_type = "quantile",
    quantile_prob = c(0.1, 0.25, 0.5, 0.75, 0.9)
  ) +
  scale_y_sqrt()
 | 
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.