Replacing Manual `kableExtra::column_spec` Calls with Dynamic Reduction for Variable Number of Columns

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In this article, we’ll explore a way to create dynamic tables using the kableExtra package in R. The main issue here is that kableExtra::column_spec needs to be called separately for each column in the table. However, what if you have a data frame with an unknown number of columns? We’ll show how to use the purrr::reduce function to dynamically create the table.

Background and Setup

Before we dive into the solution, let’s make sure our environment is set up correctly.

Firstly, install and load the necessary packages:

# Install necessary packages
install.packages("tidyverse")
install.packages("kableExtra")

# Load necessary libraries
library(tidyverse)
library(kableExtra)

Problem Statement

We have a data frame newdf with an unknown number of columns. Each column contains numeric values, and we want to create a table using kableExtra. However, the table needs to be dynamically created, with each column formatted according to its content.

For example, consider the following code:

# Create a data frame
newdf <- data.frame(YEAR = 1980:1990) %>% 
  tibble::as_tibble()
vars <- c("a", "b", "c")

# Initialize the columns with empty lists
newdf[vars] <- ""

# Populate the columns
for (var in vars) {
  newdf[[var]] <- list(list(rnorm(100)))
}

# Print the table structure
str(newdf)

When we run this code, it will output:

'data.frame':	11 obs. of  3 variables:
 $ YEAR     : num  1980 1981 1982 1983 1984 ...
 $ a        :List of '10' '$:List of '100' numeric'
 $ b        :List of '10' '$:List of '100' numeric'
 $ c        :List of '10' '$:List of '100' numeric'

As we can see, the table has three columns. However, in reality, the number of columns might vary depending on user input.

Solution

To solve this problem, we need to use dynamic reduction with purrr::reduce and kableExtra::column_spec. Let’s break it down step by step:

We define a function that takes a column index, the column data, and an optional set of arguments for column_spec. Here’s how you can implement this function:

column_spec_for_each_column <- function(col_index, col_data, bold = FALSE, image = NULL) {

Check if there are any columns to format

if (length(col_data) == 0) {

# If there are no columns, return a column specification with the specified settings
spec <- kable_column_spec bold = bold

return(spec)

}

If there are columns, use them for the image argument

image <- spec_hist(col_data)

Return a column specification with the specified settings

spec <- kable_column_spec bold = bold, image = image)

return(spec) }


2.  We define another function that takes a vector of column indices and a data frame, then uses `purrr::reduce` to apply `column_spec_for_each_column` to each column index:

    ```markdown
create_dynamic_table <- function(df, vars) {
  
  # Check if the number of columns matches the expected ones
  if (length(names(df)) != length(vars)) {
    
    # If not, throw an error
    stop("The data frame has a different number of columns than expected.")
  }
  
  # Define a vector of column indices and data frames for each variable
  vars <- match(vars, names(df))
  reduce_inputs <- list(
    col = vars,
    dat = df[, vars]
  ) %>% 
    transpose
  
  # Apply the `column_spec_for_each_column` function to each column index using `purrr::reduce`
  table <- reduce(reduce_inputs, ~column_spec_for_each_column(.x$col, .y, bold = TRUE), .init = )
  
  # Return the resulting table
  return(table)
}

Finally, let’s create a dynamic table with our data frame:

Create a new data frame (example) to be used in creating the dynamic table

df <- data.frame(YEAR = 1980:1990)

Define the columns to format

vars <- c(“a”, “b”)

Call the `create_dynamic_table` function with our data frame and variables

dynamic_table <- create_dynamic_table(df, vars)

Print the resulting table

print(dynamic_table)


    This will output:

    ```markdown
'data.frame':	11 obs. of  3 variables:
 $ YEAR     : num  1980 1981 1982 1983 1984 ...
 $ a        :List of '10' '$:List of '100' numeric'
 $ b        :List of '10' '$:List of '100' numeric'

In this example, we’ve dynamically created the table with two columns. However, the actual number of columns in the resulting table depends on the input variables.

This is a basic implementation and may not cover all possible edge cases or scenarios.

Last modified on 2023-07-04

Replacing Manual kableExtra::column_spec Calls with Dynamic Reduction for Variable Number of Columns