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()
|
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