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tickY Mark

Source: vignettes/articles/examples/marks/tickY-mark.Rmd
tickY-mark.Rmd

The tickY mark creates vertical tick marks. It’s useful for showing discrete data points, distributions, or as reference marks.

Basic Example 

# Sample data
data <- data.frame(
  category = c("A", "B", "C", "D", "E", "F", "G", "H"),
  value = c(2, 8, 3, 7, 5, 4, 6, 1)
)

spec <- list(
  plot = list(
    list(
      mark = "tickY",
      data = list(from = "sample_data"),
      x = "category",
      y = "value",
      stroke = "steelblue"
    )
  )
)

mosaic(spec, sample_data = data)

Customization Options

Custom Styling 

spec_styled <- list(
  plot = list(
    list(
      mark = "tickY",
      data = list(from = "sample_data"),
      x = "category",
      y = "value",
      stroke = "darkred",
      strokeWidth = 3
    )
  )
)

mosaic(spec_styled, sample_data = data)

Distribution Visualization 

# Random data for distribution
set.seed(123)
dist_data <- data.frame(
  group = rep(c("Group A", "Group B", "Group C"), each = 50),
  value = c(
    rnorm(50, mean = 10, sd = 2),
    rnorm(50, mean = 15, sd = 3),
    rnorm(50, mean = 12, sd = 2.5)
  )
)

spec_distribution <- list(
  plot = list(
    list(
      mark = "tickY",
      data = list(from = "dist_data"),
      x = "group",
      y = "value",
      stroke = list(column = "group"),
      strokeOpacity = 0.6
    )
  )
)

mosaic(spec_distribution, dist_data = dist_data)

Combined with Other Marks 

# Ticks with summary statistics
summary_data <- data.frame(
  category = c("A", "B", "C", "D"),
  mean_value = c(10, 15, 12, 18),
  individual_values = I(list(
    c(8, 9, 10, 11, 12),
    c(13, 14, 15, 16, 17),
    c(10, 11, 12, 13, 14),
    c(16, 17, 18, 19, 20)
  ))
)

# Expand data for individual points
expanded_data <- data.frame(
  category = rep(summary_data$category, sapply(summary_data$individual_values, length)),
  value = unlist(summary_data$individual_values)
)

spec_combined <- list(
  plot = list(
    list(
      mark = "tickY",
      data = list(from = "expanded_data"),
      x = "category",
      y = "value",
      stroke = "lightblue",
      strokeOpacity = 0.7
    ),
    list(
      mark = "dot",
      data = list(from = "summary_data"),
      x = "category",
      y = "mean_value",
      fill = "red",
      r = 4
    )
  )
)

mosaic(spec_combined, expanded_data = expanded_data, summary_data = summary_data)

Use Cases

  • Distribution Plots: Showing individual data points in distributions
  • Rug Plots: Adding marginal distributions to scatter plots
  • Data Points: Marking specific values or events
  • Reference Lines: Creating visual reference points on charts