Overview

Use ezplot to quickly create presentation-ready charts that are also useful for exploratory data analysis. By default, ezplot functions aggregate multiple values of y for repeated categories of x, group, facet_y and facet_x.

 library(ezplot)
 suppressPackageStartupMessages(library(tsibble))
 library(tsibbledata)
 suppressPackageStartupMessages(library(lubridate))
 library(ggplot2)
 library(grid)

line_plot

Weekly aggregation:

 line_plot(ansett, x = "Week", y = "Passengers")

Add grouping:

 line_plot(ansett, x = "Week", y = "Passengers", group = "Class")

Add faceting:

 line_plot(ansett, x = "Week", y = "Passengers",
 group = "Class", facet_x = "Airports",
 facet_scales = "free_y", size = 10) +
 theme(axis.text.x = element_text(angle = 90, vjust = 0.38, hjust = 1))

Plot YOY comparisons:

 line_plot(gafa_stock, "Date", c("Closing Stock Price" = "Close"),
 facet_y = "Symbol",
 facet_scales = "free_y",
 yoy = TRUE,
 labels = function(x) ez_labels(x, prepend = "$"))

Plot multiple numeric columns:

 line_plot(hh_budget,
 "Year",
 c("DI", "Expenditure", "Savings"),
 facet_x = "Country") +
 theme(panel.spacing.x = unit(1, "lines")) +
 ylab(NULL)

area_plot

Weekly aggregation:

 area_plot(ansett, x = "as.Date(Week)", y = "Passengers")

Add grouping:

 area_plot(ansett, x = "as.Date(Week)",
 y = c("Weekly Passengers" = "Passengers"),
 "Class")

Add faceting:

 area_plot(ansett,
 "year(Week) + (month(Week) - 1) / 12",
 y = c("Monthly Passengers" = "Passengers"),
 group = "substr(Airports, 5, 7)",
 facet_x = "substr(Airports, 1, 3)", facet_y = "Class",
 facet_scales = "free_y") +
 theme(axis.text.x = element_text(angle = 90, vjust = 0.38, hjust = 1))

bar_plot

Yearly aggregation

 bar_plot(subset(aus_retail, year(Month) >= 2010), 
 x = "year(Month)",
 y = "Turnover")

With grouping:

 bar_plot(subset(aus_retail, year(Month) >= 2010), 
 x = "year(Month)",
 y = "Turnover",
 group = "State",
 size = 10)