African Language Sentiment

library(tidyverse)
tuesdata <- tidytuesdayR::tt_load(2023, week = 09)

afrisenti <- tuesdata$afrisenti
languages <- tuesdata$languages



language_scripts <- tuesdata$language_scripts
language_countries <- tuesdata$language_countries
country_regions <- tuesdata$country_regions

afrisenti%>%count(label)

library(showtext)
#sysfonts::font_families_google()
sysfonts::font_add_google("Explora","Explora")
showtext_auto()

df_plot <- afrisenti%>%
  inner_join(languages,by="language_iso_code")%>%
  count(label,intended_use,language) 


  ggplot(data = df_plot, mapping = aes(label,n,fill=intended_use))+
  geom_col(width = 0.5) 
    coord_polar(theta = "y",
              start = 0,
              direction = 1, 
              clip = "off") +
  #scale_x_(clip="off")+
   #scale_x_reverse(expand=expansion(add=c(10,20))) +
   scale_y_continuous(expand=expansion(mult=c(0,0),add=c(0,1))) +
  
  labs(title="African Language Sentiment",
       caption="DataSource: #TidyTuesday 2023 week9 African Language Sentiment\nDataViz: Federica Gazzelloni #30DayChartChallenge 2023 Day11 - Circular",
       fill="Inteded use")+
scale_fill_manual(values = c("#CF3721", "#31A9B8", "#258039")) +
  theme_minimal()+
  theme(text=element_text(family="Explora",size=90,face="bold"),
        panel.grid = element_blank(),
        axis.text.y = element_blank(),
        axis.text.x = element_blank(),
        axis.title = element_blank()) +
  facet_wrap(vars(language))

ggsave("p4.png",width = 9,height = 10,
       device = "png",dpi=300,bg="white")