In-class Exercise 6: Horizon Graph

1 Overview

Building horizon plot with ggHoriPlot!

Step 1: Getting Started

Loading Libraries

pacman::p_load(ggHoriPlot, 
               ggthemes,
               tidyverse)

Importing Data

For the purpose of this hands-on exercise, Average Retail Prices Of Selected Consumer Items will be used.

averp <- read_csv("data/AVERP.csv") %>%
  mutate(`Date` = dmy(`Date`))

Step 2: Summary Statistics

Run summary statistics to determine origin and horizonscale.

summary(averp$Values)

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  0.330   2.230   3.910   8.726  12.550  68.200 

Step 3: Plotting the Horizon Graph

Origin = Midpoint

Show the code

#| fig-width: 12
#| fig-height: 10

averp %>% 
  filter(Date >= "2018-01-01") %>%
  ggplot() +
  geom_horizon(aes(x = Date, y=Values), 
               origin = "midpoint", 
               horizonscale = 6,
               show.legend = TRUE)+
  facet_grid(`Consumer Items`~.) +   #<< Each row is a facet by Consumer Item
    theme_few() +
  scale_fill_hcl(palette = 'RdBu') +
  theme(panel.spacing.y=unit(0, "lines"), strip.text.y = element_text(
    size = 5, angle = 0, hjust = 0),
    legend.position = 'Bottom',
    axis.text.y = element_blank(),
    axis.text.x = element_text(size=7),
    axis.title.y = element_blank(),
    axis.title.x = element_blank(),
    axis.ticks.y = element_blank(),
    panel.border = element_blank(),
    plot.background = element_rect(fill="#f5f5f5",colour="#f5f5f5"),
    panel.background = element_rect(fill="#f5f5f5",colour="#f5f5f5"),
    legend.background = element_rect(fill="#f5f5f5",colour="#f5f5f5"),
    strip.background =element_rect(fill="#f5f5f5")
    ) +
    scale_x_date(expand=c(0,0), date_breaks = "3 month", date_labels = "%b%y") +
  ggtitle('Average Retail Prices of Selected Consumer Items (Jan 2018 to Dec 2022)')

Origin = “Min”

Show the code

#| fig-width: 12
#| fig-height: 10
averp %>% 
  filter(Date >= "2018-01-01") %>%
  ggplot() +
  geom_horizon(aes(x = Date, y=Values), 
               origin = "min", 
               horizonscale = 6,
               show.legend = TRUE)+
  facet_grid(`Consumer Items`~.) +   #<< Each row is a facet by Consumer Item
    theme_few() +
  scale_fill_hcl(palette = 'RdBu') +
  theme(panel.spacing.y=unit(0, "lines"), strip.text.y = element_text(
    size = 5, angle = 0, hjust = 0),
    legend.position = 'Bottom',
    axis.text.y = element_blank(),
    axis.text.x = element_text(size=7),
    axis.title.y = element_blank(),
    axis.title.x = element_blank(),
    axis.ticks.y = element_blank(),
    panel.border = element_blank(),
    plot.background = element_rect(fill="#f5f5f5",colour="#f5f5f5"),
    panel.background = element_rect(fill="#f5f5f5",colour="#f5f5f5"),
    legend.background = element_rect(fill="#f5f5f5",colour="#f5f5f5"),
    strip.background =element_rect(fill="#f5f5f5")
    ) +
    scale_x_date(expand=c(0,0), date_breaks = "3 month", date_labels = "%b%y") +
  ggtitle('Average Retail Prices of Selected Consumer Items (Jan 2018 to Dec 2022)')

Horizon Scale = 10

averp %>% 
  filter(Date >= "2018-01-01") %>%
  ggplot() +
  geom_horizon(aes(x = Date, y=Values), 
               origin = "midpoint", 
               horizonscale = 10,
               show.legend = TRUE)+
  facet_grid(`Consumer Items`~.) +   #<< Each row is a facet by Consumer Item
    theme_few() +
  scale_fill_hcl(palette = 'RdBu') +
  theme(panel.spacing.y=unit(0, "lines"), strip.text.y = element_text(
    size = 5, angle = 0, hjust = 0),
    legend.position = 'Bottom',
    axis.text.y = element_blank(),
    axis.text.x = element_text(size=7),
    axis.title.y = element_blank(),
    axis.title.x = element_blank(),
    axis.ticks.y = element_blank(),
    panel.border = element_blank(),
    plot.background = element_rect(fill="#f5f5f5",colour="#f5f5f5"),
    panel.background = element_rect(fill="#f5f5f5",colour="#f5f5f5"),
    legend.background = element_rect(fill="#f5f5f5",colour="#f5f5f5"),
    strip.background =element_rect(fill="#f5f5f5")
    ) +
    scale_x_date(expand=c(0,0), date_breaks = "3 month", date_labels = "%b%y") +
  ggtitle('Average Retail Prices of Selected Consumer Items (Jan 2018 to Dec 2022)')