Visualizing agricultural data using conditionally formatted tables

Using the {gt} package to visualize data in tables
R
#TidyTuesday
gt
Author

Mickey Rafa

Published

December 30, 2022

Figure 1: Maize yield of countries in the Southern African Development Community from 2010 to 2018. This table is conditionally formatted to highlight values of higher maize yield in this subset of data. Source: Our World in Data.

1. Load Packages & Setup

Show code
if (!require("pacman")) install.packages("pacman")
pacman::p_load(
    tidyverse,
    tidytuesdayR,
    dlookr,
    ggtext,
    countrycode,
    gt,
    gtExtras,  #for font awesome icons in gt tables
    ggbump,
    showtext,
    janitor,   #for clean_names()
    scales,
    htmltools, #for tagList()
    glue,
    here,
    geomtextpath
)

2. Read in the Data

Show code
tt_year <- 2020
tt_week <- 36

tuesdata <- tidytuesdayR::tt_load(tt_year, week = tt_week)

yield <- tuesdata$key_crop_yields

3. Examine the Data

Show code
yield %>% 
  glimpse()
Rows: 13,075
Columns: 14
$ Entity                             <chr> "Afghanistan", "Afghanistan", "Afgh…
$ Code                               <chr> "AFG", "AFG", "AFG", "AFG", "AFG", …
$ Year                               <dbl> 1961, 1962, 1963, 1964, 1965, 1966,…
$ `Wheat (tonnes per hectare)`       <dbl> 1.0220, 0.9735, 0.8317, 0.9510, 0.9…
$ `Rice (tonnes per hectare)`        <dbl> 1.5190, 1.5190, 1.5190, 1.7273, 1.7…
$ `Maize (tonnes per hectare)`       <dbl> 1.4000, 1.4000, 1.4260, 1.4257, 1.4…
$ `Soybeans (tonnes per hectare)`    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ `Potatoes (tonnes per hectare)`    <dbl> 8.6667, 7.6667, 8.1333, 8.6000, 8.8…
$ `Beans (tonnes per hectare)`       <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ `Peas (tonnes per hectare)`        <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ `Cassava (tonnes per hectare)`     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ `Barley (tonnes per hectare)`      <dbl> 1.0800, 1.0800, 1.0800, 1.0857, 1.0…
$ `Cocoa beans (tonnes per hectare)` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ `Bananas (tonnes per hectare)`     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA,…

The dataset contains yeild data across a variety of crop types and includes countries, territories, and regions. I want to narrow this to look at only corn yields in countries in the Southern African Development Community.

4. Tidy the Data

Show code
yield <- yield %<>% 
  janitor::clean_names() %>% 
  left_join(x=.,
            y=countrycode::codelist %>% 
              select(continent, iso3c, un.regionsub.name) %>% 
              filter(complete.cases(.)),
            by=c('code' = 'iso3c')) %>% 
  gather(crop, yield, 4:14) %>% 
  mutate(decade = as.factor(year - (year %% 10)),
         crop = str_to_title(str_remove(crop, "_tonnes_per_hectare")))

sadc <- c('Angola', 'Botswana', 'Comoros', 
          'Democratic Republic of Congo', 'Swaziland', 
          'Lesotho', 'Madagascar', 'Malawi', 'Mauritius',
          'Mozambique', 'Namibia', 'Seychelles', 
          'South Africa', 'Tanzania', 'Zambia', 'Zimbabwe')

yield_df <- yield %>% 
  filter(decade == '2010',
         entity %in% sadc) %>% 
  select(-c(decade, continent, code, un.regionsub.name)) %>% 
  spread(year, yield) %>% 
  rename(country = entity) %>%
  filter(crop == 'Maize') %>% 
  select(-crop)

5. Visualization Parameters

Show code
title_text <- md("**Maize Yields in the Southern African Development Community**")

subtitle_text <- md("*in tons per hectare* between 2010 and 2018")

source_text <-  md("**Source**: Our World In Data<br>**Inspiration**: https://themockup.blog/posts/2020-09-04-10-table-rules-in-r/")

6. Plot

Show code
yield_gt <- yield_df %>% 
  gt(rowname_col = 'country') %>% 
  fmt_number(columns = 2:last_col(),
             decimals = 1) %>% 
  sub_missing(columns = 2:last_col(),
              missing_text = '-') %>% 
  tab_header(title = title_text,
             subtitle = subtitle_text) %>% 
  data_color(
    columns = 2:last_col(),
    colors = 
      scales::col_numeric(
        paletteer::paletteer_d(
          palette = "ggsci::green_material") %>% 
          as.character(),
        domain = NULL)) %>% 
  opt_table_font(
    font = list(
      google_font("Rubik"),
      default_fonts()
    )) %>% 
  tab_source_note(source_note = source_text) %>% 
  tab_options(
    heading.subtitle.font.size = 12,
    heading.align = "left",
    table.border.top.color = "black",
    column_labels.border.bottom.color = "black",
    column_labels.border.bottom.width= px(3))

7. Save

Show code
# Save the plot as PNG
yield_gt %>% 
  gtsave(
  filename = glue("tt_{tt_year}_{tt_week}.png"),
  path = here::here()
)

# make thumbnail for page
magick::image_read(glue("tt_{tt_year}_{tt_week}.png")) %>%
  magick::image_resize(geometry = "400") %>%
  magick::image_write(glue("tt_{tt_year}_{tt_week}_thumbnail.png"))

8. Session Info

R version 4.4.0 (2024-04-24)
Platform: aarch64-apple-darwin20
Running under: macOS Sonoma 14.6.1

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: America/Denver
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] geomtextpath_0.1.4 here_1.0.1         glue_1.8.0         htmltools_0.5.8.1 
 [5] scales_1.3.0       janitor_2.2.0      showtext_0.9-7     showtextdb_3.0    
 [9] sysfonts_0.8.9     ggbump_0.1.0       gtExtras_0.5.0     gt_0.11.1         
[13] countrycode_1.6.0  ggtext_0.1.2       dlookr_0.6.3       tidytuesdayR_1.1.2
[17] lubridate_1.9.3    forcats_1.0.0      stringr_1.5.1      dplyr_1.1.4       
[21] purrr_1.0.2        readr_2.1.5        tidyr_1.3.1        tibble_3.2.1      
[25] ggplot2_3.5.1      tidyverse_2.0.0    pacman_0.5.1      

loaded via a namespace (and not attached):
 [1] gridExtra_2.3           httr2_1.0.5             rematch2_2.1.2         
 [4] rlang_1.1.4             magrittr_2.0.3          hrbrthemes_0.8.7       
 [7] snakecase_0.11.1        compiler_4.4.0          systemfonts_1.1.0      
[10] vctrs_0.6.5             pkgconfig_2.0.3         crayon_1.5.3           
[13] fastmap_1.2.0           magick_2.8.5            fontawesome_0.5.2      
[16] utf8_1.2.4              promises_1.3.0          rmarkdown_2.28         
[19] markdown_1.13           tzdb_0.4.0              ps_1.8.0               
[22] bit_4.5.0               xfun_0.48               jsonlite_1.8.9         
[25] later_1.3.2             parallel_4.4.0          R6_2.5.1               
[28] stringi_1.8.4           pagedown_0.21           extrafontdb_1.0        
[31] Rcpp_1.0.13             knitr_1.48              base64enc_0.1-3        
[34] extrafont_0.19          gitcreds_0.1.2          httpuv_1.6.15          
[37] timechange_0.3.0        tidyselect_1.2.1        rstudioapi_0.17.1      
[40] yaml_2.3.10             websocket_1.4.2         processx_3.8.4         
[43] curl_5.2.3              shiny_1.9.1             withr_3.0.1            
[46] evaluate_1.0.1          xml2_1.3.6              pillar_1.9.0           
[49] generics_0.1.3          vroom_1.6.5             rprojroot_2.0.4        
[52] chromote_0.3.1          paletteer_1.6.0         hms_1.1.3              
[55] munsell_0.5.1           commonmark_1.9.2        xtable_1.8-4           
[58] gdtools_0.4.0           webshot2_0.1.1          tools_4.4.0            
[61] reactable_0.4.4         fs_1.6.4                grid_4.4.0             
[64] Rttf2pt1_1.3.12         gh_1.4.1                colorspace_2.1-1       
[67] cli_3.6.3               rappdirs_0.3.3          kableExtra_1.4.0       
[70] textshaping_0.4.0       fontBitstreamVera_0.1.1 fansi_1.0.6            
[73] viridisLite_0.4.2       svglite_2.1.3           gtable_0.3.5           
[76] sass_0.4.9              digest_0.6.37           fontquiver_0.2.1       
[79] prismatic_1.1.2         htmlwidgets_1.6.4       farver_2.1.2           
[82] lifecycle_1.0.4         mime_0.12               fontLiberation_0.1.0   
[85] gridtext_0.1.5          bit64_4.5.2

9. Github Repository