library(gapminder)
library(dplyr)
library(tidyr)
library(stringr)
library(purrr)
library(gt)
library(mmtable2)

Formatting tables

mmtable2 outputs tables using the gt package’s format.

This means you can alter formatting using many existing gt styling commands.

gm_table_formatted <- 
gapminder_mm %>% 
  filter(var != "Life expectancy") %>% 
  mmtable(cells = value) +
  header_top(year) +
  header_left(country) +
  header_top_left(var)  +
  header_left_top(continent)  +
  cells_format(cell_predicate = T, style = list(cell_text(align = "right"))) +
  header_format(header = year, style = list(cell_text(align = "right"))) +
  header_format("all_cols", style = list(cell_text(weight = "bolder"))) +
  header_format("all_rows", style = list(cell_text(weight = "bolder"))) +
  header_format(continent,scope = "table",style = list(cell_borders(sides = "top",color = "grey"))) 

print(gm_table_formatted)

		GDP				Population
		1992	1997	2002	2007	1992	1997	2002	2007
Africa	Botswana	8.0	8.6	11.0	12.6	1.3	1.5	1.6	1.6
	Gabon	13.5	14.7	12.5	13.2	1.0	1.1	1.3	1.5
Americas	Canada	26.3	29.0	33.3	36.3	28.5	30.3	31.9	33.4
	United States	32.0	35.8	39.1	43.0	256.9	272.9	287.7	301.1
Asia	Kuwait	34.9	40.3	35.1	47.3	1.4	1.8	2.1	2.5
	Singapore	24.8	33.5	36.0	47.1	3.2	3.8	4.2	4.6
Europe	Ireland	17.6	24.5	34.1	40.7	3.6	3.7	3.9	4.1
	Norway	34.0	41.3	44.7	49.4	4.3	4.4	4.5	4.6
Oceania	Australia	23.4	27.0	30.7	34.4	17.5	18.6	19.5	20.4
	New Zealand	18.4	21.1	23.2	25.2	3.4	3.7	3.9	4.1

Merged header columns

Table headers can be merged with header_merged_cols(). This supports an aributrary number of column headers.

style_list <- list(cell_borders(sides = "top",color = "lightgrey",weight = px(3)))
gm_df <- gapminder_mm %>% filter(var != "Life expectancy")
style_list3 = list(cell_text(align = "left"))

gm_table_merged <- 
 gm_df %>% 
  mmtable(cells = value) +
  header_left(year) +
  header_top(country) +
  header_left_top(var)  +
  header_top_left(continent)  +
  header_format(var,scope = "table",style = style_list) +
  header_format(continent,style_list3 ) +
  header_merged_cols()

 print(gm_table_merged)

		Africa		Americas		Asia		Europe		Oceania
		Botswana	Gabon	Canada	United States	Kuwait	Singapore	Ireland	Norway	Australia	New Zealand
GDP	1992	8.0	13.5	26.3	32.0	34.9	24.8	17.6	34.0	23.4	18.4
	1997	8.6	14.7	29.0	35.8	40.3	33.5	24.5	41.3	27.0	21.1
	2002	11.0	12.5	33.3	39.1	35.1	36.0	34.1	44.7	30.7	23.2
	2007	12.6	13.2	36.3	43.0	47.3	47.1	40.7	49.4	34.4	25.2
Population	1992	1.3	1.0	28.5	256.9	1.4	3.2	3.6	4.3	17.5	3.4
	1997	1.5	1.1	30.3	272.9	1.8	3.8	3.7	4.4	18.6	3.7
	2002	1.6	1.3	31.9	287.7	2.1	4.2	3.9	4.5	19.5	3.9
	2007	1.6	1.5	33.4	301.1	2.5	4.6	4.1	4.6	20.4	4.1

Alternative pipe syntax

Adding the add_ prefix to functions allows use of %>% in place of +.

gm_table_piped <- 
gapminder_mm %>% 
  filter(var != "Life expectancy") %>% 
  mmtable(cells = value, use_default_formats = T) %>% 
  add_header_top(year) %>% 
  add_header_left(country) %>% 
  add_header_top_left(var)  %>% 
  add_header_left_top(continent)  %>% 
  add_cells_format(cell_predicate = T, style = list(cell_text(align = "right"))) %>% 
  add_header_format(header = year, style = list(cell_text(align = "right"))) %>% 
  add_header_format("all_cols", style = list(cell_text(weight = "bolder"))) %>% 
  add_header_format("all_rows", style = list(cell_text(weight = "bolder"))) %>% 
  add_header_format(continent,scope = "table",style = style_list) 

print(gm_table_piped)

		GDP				Population
		1992	1997	2002	2007	1992	1997	2002	2007
Africa	Botswana	8.0	8.6	11.0	12.6	1.3	1.5	1.6	1.6
	Gabon	13.5	14.7	12.5	13.2	1.0	1.1	1.3	1.5
Americas	Canada	26.3	29.0	33.3	36.3	28.5	30.3	31.9	33.4
	United States	32.0	35.8	39.1	43.0	256.9	272.9	287.7	301.1
Asia	Kuwait	34.9	40.3	35.1	47.3	1.4	1.8	2.1	2.5
	Singapore	24.8	33.5	36.0	47.1	3.2	3.8	4.2	4.6
Europe	Ireland	17.6	24.5	34.1	40.7	3.6	3.7	3.9	4.1
	Norway	34.0	41.3	44.7	49.4	4.3	4.4	4.5	4.6
Oceania	Australia	23.4	27.0	30.7	34.4	17.5	18.6	19.5	20.4
	New Zealand	18.4	21.1	23.2	25.2	3.4	3.7	3.9	4.1

Working with colors

mmtable2 uses the style features of gt. This gives you a lot of control over the format of your table. As an example, a rainbow histogram is constructed below.

Data generation

The code below generates a set of random numbers and bins them in 10s.

library(mmtable2)
library(tidyverse)

set.seed(123)
df <- 
tibble(data = rnorm(100,100,30) %>% round()) %>% 
  mutate(rounded = floor(data/10)*10) %>% 
  mutate(rounded_chr = paste0(rounded,"'s"))  %>% 
  arrange(rounded,desc(data))

df %>% glimpse
#> Rows: 100
#> Columns: 3
#> $ data        <dbl> 31, 49, 41, 54, 69, 69, 69, 68, 68, 66, 66, 63, 62, 62, 79…
#> $ rounded     <dbl> 30, 40, 40, 50, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 70…
#> $ rounded_chr <chr> "30's", "40's", "40's", "50's", "60's", "60's", "60's", "6…

Table construction

The code below constructs a table with these values, and then adds a list of formatting commands.

# Generate random data 
df <- 
tibble(data = rnorm(100,100,30) %>% round()) %>% 
  mutate(rounded = floor(data/10)*10) %>% 
  mutate(rounded_chr = paste0(rounded,"'s"))  %>% 
  arrange(rounded,desc(data))

# Create table  
table <- 
df %>% 
  mmtable(cells = data) +
  header_top_left(rounded_chr) + 
  header_format(rounded_chr, 
                list(gt::cell_fill(color = "black"),
                     gt::cell_text(color = "white")))

# Format table
colors <-  c("#ff0000","#ffa500","#ffff00","#008000",
             "#0000ff","#4b0082","#ee82ee")
color_list <- 
  map2(unique(df$rounded_chr),rep(colors,2), 
       function(nums,colours){
        cells_format(cell_predicate =nchar(data) %in% c(2,3) & 
                     rounded_chr == nums, 
                     gt::cell_fill(color = colours))
         }
       )

print(append(list(table),color_list) %>% reduce(`+`))