Puntuación por taza de café (CQI)

Important

EN

This chart highlights the five countries with the highest coffee production in the world, taking into account various quality measures: aroma, flavor, aftertaste, acidity, body, balance, uniformity, cup cleanliness, sweetness, moisture, and defects.

Important

ES

En este gráfico destacan los cinco países con mayor producción de café en el mundo, tomando en cuenta varias medidas de calidad: aroma, sabor, regusto, acidez, cuerpo, balance, uniformidad, limpieza de la taza, dulzura, humedad y defectos.

Important

IT

IT Questo grafico evidenzia i cinque paesi con la più alta produzione di caffè al mondo, tenendo conto di vari parametri di qualità: aroma, sapore, retrogusto, acidità, corposità, equilibrio, uniformità, pulizia della tazza, dolcezza, umidità e difetti.

# LIBRARIES
library(tidyverse)
library(ggpubr)
library(reshape2)
library(ggcorrplot)
library(ggcharts)
library(tmaptools)
library(prismatic)
library(patchwork)
library(gridExtra)
library(ggflags)
library(showtext)
library(camcorder)
library(ggtext)


# FONTS
font_add_google("Luckiest Guy","ramp")
font_add_google("Bebas Neue","beb")
font_add_google("Fira Sans","fira")
font_add_google("Raleway","ral")
font_add_google("Bitter","bit")
showtext_auto()


# DATA
coffee_ratings <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-07-07/coffee_ratings.csv')
coffee_ratings = data.frame(coffee_ratings, stringsAsFactors = FALSE)

coffee_ratings <- coffee_ratings %>%
  filter(country_of_origin %in% c("Brazil", "Vietnam", "Colombia", "Indonesia", "Ethiopia")) 

coffee_ratings <- coffee_ratings %>%
  mutate(iso3 = countrycode::countrycode(country_of_origin,
                                         origin = "country.name.en",
                                         destination = "iso3c"))


data2 <- tibble(
  count = c(1,1,1,1,1),
  n = c(1,2,3,4,5),
  country =c("Brazil", "Vietnam", "Colombia", "Indonesia", "Ethiopia"),
  code =c("br","vn","co","id","et"))

data1 <- coffee_ratings %>%
  mutate(iso3 = countrycode::countrycode(country_of_origin,
                                         origin = "country.name.en",
                                         destination = "iso3c"))

# PLOT

p1 <- ggplot(data=coffee_ratings) + 
  #annotation_custom(grob = g, xmin = -Inf, xmax = Inf, ymin = -Inf, ymax = Inf) + 
  xlim(69,90) +
  geom_violin(aes(y = country_of_origin, x = total_cup_points), color=NA, alpha=.95 ) +
  geom_jitter(aes(y = country_of_origin, x = total_cup_points),
              height = .2, size = 4,
              alpha = .5,
              color = "#daa520")  +
  geom_boxplot(aes(y = country_of_origin, x = total_cup_points),
               alpha = 0,
               outlier.shape = NA,
               coef = 0,
               color = "#daa520",
               fill = "red") +
  geom_vline(xintercept = mean(coffee_ratings$total_cup_points),
             linetype = 2,
             size = 0.5, col="red") +
  geom_curve(x = 83.5, y = 5, xend = 87, yend = 5.1)+
  annotate("text", label = "Valoración media\nde todos los países productores", x = 87, y = 5.3, family = "fira") +
  geom_segment(aes(x = mean(total_cup_points), 
                   y = country_of_origin, 
                   yend= country_of_origin, xend=  83, 
                   col="red" )) +
  geom_point(aes(y = country_of_origin, x = mean(total_cup_points)),
             size = 4, col = "red") +
  labs(title = "\nPuntuación por taza de café (CQI: 2010 - 2018)",
       subtitle = "Mayores productores de café del mundo\nDatos: Coffee Quality Institute (CQI) 2010-2018\n\nMedidas de calidad: aroma, sabor, regusto, acidez, cuerpo, balance,\nuniformidad, limpieza de la taza, dulzura, humedad y defectos\n",
       caption = "") +
  xlab("\nPuntuación por taza") +
  ylab(" ") +
  geom_flag(data=data2, aes(y=country,  x=70,
                            country=code), size=25 ) +
  theme(legend.position = "none",
        panel.grid.major = element_line(size = 0.1, linetype = 'solid',
                                        colour = "white"), 
        panel.grid.minor = element_line(size = 0.1, linetype = 'solid',
                                        colour = "white"),
        axis.title.x=element_text(size=16, family = "fira"),
        plot.title=element_text(size=25, family = "bit", color = "#190706"),
        axis.text.y  = element_text(color = "#190706", size=14, family = "fira"),
        axis.text.x  = element_text(color = "#190706", size=12, family = "fira"),
  )

#p1