What’s the best coffee?

tidytuesday
code
analysis
Author

Camilo García-Botero

Published

July 20, 2020

Modified

September 10, 2023

Introduction

This is my first Tidy Tuesday contribution and will be playing around a little bit with the coffee rating data.

As a coffee lover I felt that exploring a dataset about coffee was mandatory. The first question that came to me mind was: what is the best coffee and eventually, as looking a little bit deeper into dataset, which country has the best coffees.

I decided then to compare coffee ratings across countries and the associated density of cups rated. Among the main findings it shows that one Ethiopian coffee came to be the best ranked and also that this country’s coffees are the best ranked while Haitian coffees show one of the widest range of ratings. Colombian coffee display a moderately good ratings and a very narrow range.

Coffee rating distributions

coffee <- read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-07-07/coffee_ratings.csv')

head(coffee) |>
 kable()
total_cup_points species owner country_of_origin farm_name lot_number mill ico_number company altitude region producer number_of_bags bag_weight in_country_partner harvest_year grading_date owner_1 variety processing_method aroma flavor aftertaste acidity body balance uniformity clean_cup sweetness cupper_points moisture category_one_defects quakers color category_two_defects expiration certification_body certification_address certification_contact unit_of_measurement altitude_low_meters altitude_high_meters altitude_mean_meters
90.58 Arabica metad plc Ethiopia metad plc NA metad plc 2014/2015 metad agricultural developmet plc 1950-2200 guji-hambela METAD PLC 300 60 kg METAD Agricultural Development plc 2014 April 4th, 2015 metad plc NA Washed / Wet 8.67 8.83 8.67 8.75 8.50 8.42 10 10 10 8.75 0.12 0 0 Green 0 April 3rd, 2016 METAD Agricultural Development plc 309fcf77415a3661ae83e027f7e5f05dad786e44 19fef5a731de2db57d16da10287413f5f99bc2dd m 1950 2200 2075
89.92 Arabica metad plc Ethiopia metad plc NA metad plc 2014/2015 metad agricultural developmet plc 1950-2200 guji-hambela METAD PLC 300 60 kg METAD Agricultural Development plc 2014 April 4th, 2015 metad plc Other Washed / Wet 8.75 8.67 8.50 8.58 8.42 8.42 10 10 10 8.58 0.12 0 0 Green 1 April 3rd, 2016 METAD Agricultural Development plc 309fcf77415a3661ae83e027f7e5f05dad786e44 19fef5a731de2db57d16da10287413f5f99bc2dd m 1950 2200 2075
89.75 Arabica grounds for health admin Guatemala san marcos barrancas “san cristobal cuch NA NA NA NA 1600 - 1800 m NA NA 5 1 Specialty Coffee Association NA May 31st, 2010 Grounds for Health Admin Bourbon NA 8.42 8.50 8.42 8.42 8.33 8.42 10 10 10 9.25 0.00 0 0 NA 0 May 31st, 2011 Specialty Coffee Association 36d0d00a3724338ba7937c52a378d085f2172daa 0878a7d4b9d35ddbf0fe2ce69a2062cceb45a660 m 1600 1800 1700
89.00 Arabica yidnekachew dabessa Ethiopia yidnekachew dabessa coffee plantation NA wolensu NA yidnekachew debessa coffee plantation 1800-2200 oromia Yidnekachew Dabessa Coffee Plantation 320 60 kg METAD Agricultural Development plc 2014 March 26th, 2015 Yidnekachew Dabessa NA Natural / Dry 8.17 8.58 8.42 8.42 8.50 8.25 10 10 10 8.67 0.11 0 0 Green 2 March 25th, 2016 METAD Agricultural Development plc 309fcf77415a3661ae83e027f7e5f05dad786e44 19fef5a731de2db57d16da10287413f5f99bc2dd m 1800 2200 2000
88.83 Arabica metad plc Ethiopia metad plc NA metad plc 2014/2015 metad agricultural developmet plc 1950-2200 guji-hambela METAD PLC 300 60 kg METAD Agricultural Development plc 2014 April 4th, 2015 metad plc Other Washed / Wet 8.25 8.50 8.25 8.50 8.42 8.33 10 10 10 8.58 0.12 0 0 Green 2 April 3rd, 2016 METAD Agricultural Development plc 309fcf77415a3661ae83e027f7e5f05dad786e44 19fef5a731de2db57d16da10287413f5f99bc2dd m 1950 2200 2075
88.83 Arabica ji-ae ahn Brazil NA NA NA NA NA NA NA NA 100 30 kg Specialty Coffee Institute of Asia 2013 September 3rd, 2013 Ji-Ae Ahn NA Natural / Dry 8.58 8.42 8.42 8.50 8.25 8.33 10 10 10 8.33 0.11 0 0 Bluish-Green 1 September 3rd, 2014 Specialty Coffee Institute of Asia 726e4891cf2c9a4848768bd34b668124d12c4224 b70da261fcc84831e3e9620c30a8701540abc200 m NA NA NA 
coffee |>
  drop_na(any_of("country_of_origin")) |>
  filter(aroma != 0 & !country_of_origin %in% c("Zambia", "Rwanda", "Papua New Guinea", "Japan", "Mauritius", "Cote d?Ivoire", "Burundi")) |>
  mutate(country_of_origin = fct_reorder(country_of_origin, total_cup_points)) |> 
  ggplot(aes(x = total_cup_points, y = country_of_origin, fill = stat(x), label = owner)) +
  geom_density_ridges_gradient(show.legend = T, alpha = .5, point_alpha = 0.5, jittered_points = TRUE) +
  theme_ipsum() +
  scale_fill_viridis_c(alpha = 0.7) +
  ylab("") +
  xlab("Total cup points") +
  labs(
    title = "Comparison of coffee's ratings across countries and its distribution",
    subtitle = "Ethiopian coffees seem to be the best. Latinoamerican countries were more abundant in the competition",
    caption = "Data: TidyTuesday week 28. Plot: @Gaspardelanoche",
    fill = "Total cup points"
  ) +
  theme(
    plot.title = element_text(size = 20, face = "bold"),
    plot.subtitle = element_text(size = 18),
    axis.title.x = element_text(size = 18),
    axis.title.y = element_text(size = 18),
    axis.text.y = element_text(size = 18),
    plot.caption = element_text(size = 16)
  ) +
  geom_label_repel(
    data = subset(coffee, total_cup_points > 89),
    force = 10,
    xlim = c(85, NA)
  )
Picking joint bandwidth of 0.919

Citation

BibTeX citation:
@misc{garcía-botero2020,
  author = {García-Botero, Camilo},
  title = {What’s the Best Coffee?},
  date = {2020-07-20},
  url = {https://camilogarciabotero.github.io/blog},
  langid = {en}
}
For attribution, please cite this work as:
García-Botero, Camilo. 2020. “What’s the Best Coffee?” https://camilogarciabotero.github.io/blog.