print.gran_advice {gravitas}

Advice summaries for granularities

Description

Recommendations on plot choices, interaction, number of observations and intra or inter facet homogeneity. Important summaries before drawing distribution plots.

Usage

## S3 method for class 'gran_advice'
print(x, ...)

Arguments

x

An object of class gran_advice

...

other arguments to be passed for appropriate labels.

Value

Print check points before visualizing distribution across bivariate granularities

Examples

library(dplyr)
library(ggplot2)

smart_meter10 %>%
filter(customer_id == "10017936") %>%
  gran_advice(gran1 = "wknd_wday",
            gran2 = "hour_day")