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Create a Summary Table and Plot of Code Frequencies

Source: R/create_code_summary.R
create_code_summary.Rd

Summarizes how often each qualitative code (represented by logical 0/1 variables) appears across excerpts or media titles. Optionally produces a frequency table and visualization of code distributions.

This function automatically handles Stata-labelled (haven_labelled) or numeric 0/1 variables by converting them to logicals. You can also pass in a custom codebook to apply human-readable code labels.

Usage

create_code_summary(
  excerpts,
  table_min_count = 1,
  table_min_prop = NULL,
  plot = FALSE,
  plot_min_count = NULL,
  plot_min_prop = NULL,
  output_type = c("tibble", "kable", "datatable"),
  exclude = NULL,
  plot_metric = c("count", "prop", "both"),
  fill_color = "steelblue",
  use_labels = FALSE,
  codebook = NULL
)

Arguments

excerpts

A data frame containing at least one logical or 0/1 variable representing a code, and a column named media_title that identifies the source document or excerpt.

table_min_count

Minimum number of excerpts required for a code to appear in the summary table. Default is 1.

table_min_prop

Optional proportion threshold (relative to the maximum count) for including codes in the table. Default is NULL.

plot

Logical; whether to generate a plot visualizing code frequencies. Default is FALSE.

plot_min_count

Minimum number of excerpts required for a code to appear in the plot. Defaults to table_min_count.

plot_min_prop

Optional proportion threshold (relative to the maximum count) for including codes in the plot. Defaults to table_min_prop.

output_type

The format for the output table. One of "tibble", "kable", or "datatable". Default is "tibble".

exclude

Optional character vector of variable names to exclude from analysis.

plot_metric

The metric to visualize. One of "count", "prop", or "both". Default is "count".

fill_color

Color for plot bars. Default is "steelblue".

use_labels

Logical; if TRUE, uses a supplied codebook to display descriptive labels for codes instead of variable names. Default is FALSE.

codebook

Optional data frame with two columns:

  • variable: the variable names in the dataset

  • label: the corresponding human-readable label for each code. Required when use_labels = TRUE.

Value

If plot = FALSE, returns a table in the selected output_type format. If plot = TRUE, invisibly returns a list with two elements:

table

A table of summarized code frequencies.

plot

A ggplot object visualizing the results.

Details

The function first identifies all logical (or 0/1 numeric) columns in excerpts and calculates:

  • count: total number of excerpts where the code is applied

  • n_media_titles: number of distinct media titles containing the code

  • prop_media_titles: proportion of media titles containing the code (relative to max)

The table can be output as a tibble, formatted table (knitr::kable), or interactive data table (DT::datatable).

When plot = TRUE, the function generates a ggplot2 bar chart showing either code counts, proportions, or both (dual-axis view).

Examples

# Example 1: Basic usage without a codebook
df <- data.frame(
  media_title = c("Doc1", "Doc2", "Doc3", "Doc4"),
  code_a = c(TRUE, FALSE, TRUE, TRUE),
  code_b = c(FALSE, TRUE, TRUE, FALSE)
)

create_code_summary(df, plot = TRUE)
#> # A tibble: 2 × 4
#>   code   count n_media_titles prop_media_titles
#>   <chr>  <int>          <int>             <dbl>
#> 1 code_a     3              3              1   
#> 2 code_b     2              2              0.67

# Example 2: Using a codebook for readable labels
codebook <- data.frame(
  variable = c("code_a", "code_b"),
  label = c("Community Engagement", "Policy Support")
)

create_code_summary(
  df,
  use_labels = TRUE,
  codebook = codebook,
  plot = TRUE,
  plot_metric = "both"
)
#> # A tibble: 2 × 4
#>   code                 count n_media_titles prop_media_titles
#>   <chr>                <int>          <int>             <dbl>
#> 1 Community Engagement     3              3              1   
#> 2 Policy Support           2              2              0.67

# Example 3: Excluding a code and outputting as datatable
create_code_summary(
  df,
  exclude = "code_b",
  output_type = "datatable"
)