Skip to contents

Compute and Visualize Code Saturation

Source: R/set_saturation.R
set_saturation.Rd

This function summarizes code counts and their proportional representation across media titles (e.g., interviews, focus groups, or other qualitative data sources). It can optionally produce a formatted table and/or a ggplot visualization showing saturation by code frequency or proportion.

Usage

set_saturation(
  code_counts,
  total_media_titles = NULL,
  table_min_count = 1,
  table_min_prop = NULL,
  output_type = c("tibble", "kable"),
  plot = FALSE,
  plot_min_count = NULL,
  plot_min_prop = NULL,
  plot_metric = c("prop", "count", "both"),
  fill_color = "steelblue"
)

Arguments

code_counts

A tibble or data frame containing columns:

  • code: the code label

  • count: total number of excerpts coded with that code

  • n_media_titles: number of distinct media titles (e.g., transcripts) in which the code appears. This object is typically generated by create_code_summary().

total_media_titles

Optional numeric value indicating the total number of media titles. If NULL (default), the function uses the maximum value of n_media_titles.

table_min_count

Minimum count threshold for including a code in the output table. Defaults to 1.

table_min_prop

Minimum proportion threshold (relative to total media titles) for including a code in the output table. Defaults to NULL (no proportion filter).

output_type

Character string indicating the output format for the table: either "tibble" (default) or "kable".

plot

Logical; if TRUE, produces a ggplot visualization. Defaults to FALSE.

plot_min_count

Minimum count threshold for codes to include in the plot. Defaults to table_min_count if NULL.

plot_min_prop

Minimum proportion threshold for codes to include in the plot. Defaults to table_min_prop if NULL.

plot_metric

Character string indicating what to plot: "prop" for proportions, "count" for counts, or "both" for dual-axis plot. Defaults to "prop".

fill_color

Character string specifying the fill color for bars in the plot. Defaults to "steelblue".

Value

  • If plot = FALSE: returns a tibble (or kable table) summarizing code frequencies and proportions.

  • If plot = TRUE: returns a list with two elements:

    • table: the filtered tibble

    • plot: a ggplot2 object.

Examples

# Example dataset
code_counts <- tibble::tibble(
  code = c("Belonging", "Resilience", "Stress", "Hope"),
  count = c(15, 10, 8, 5),
  n_media_titles = c(8, 6, 5, 3)
)

# Basic usage (returns a tibble)
set_saturation(code_counts)
#> # A tibble: 4 × 3
#>   code       count prop_media_titles
#>   <chr>      <dbl>             <dbl>
#> 1 Belonging     15              1   
#> 2 Resilience    10              0.75
#> 3 Stress         8              0.62
#> 4 Hope           5              0.38

# Apply count and proportion filters, return a kable table
set_saturation(
  code_counts,
  total_media_titles = 10,
  table_min_count = 5,
  table_min_prop = 0.3,
  output_type = "kable"
)
#> 
#> 
#> Table: Code Counts with Transcript Proportions (table_min_count = 5 , table_min_prop = 0.3 )
#> 
#> |code       | count| prop_media_titles|
#> |:----------|-----:|-----------------:|
#> |Belonging  |    15|               0.8|
#> |Resilience |    10|               0.6|
#> |Stress     |     8|               0.5|
#> |Hope       |     5|               0.3|

# Generate a plot of proportions
res <- set_saturation(
  code_counts,
  total_media_titles = 10,
  plot = TRUE,
  plot_metric = "prop"
)
res$plot


# Plot both count and proportion using dual y-axes
res <- set_saturation(
  code_counts,
  total_media_titles = 10,
  plot = TRUE,
  plot_metric = "both",
  fill_color = "darkgreen"
)
res$plot