Down upwards

To cite Federica’s work, please use: Gazzelloni F., 2023 Data Visualization US Egg Production down/upwards

library(tidyverse)
tuesdata <- tidytuesdayR::tt_load(2023, week = 15)

eggs <- tuesdata$`egg-production`
cages <- tuesdata$`cage-free-percentages`

eggs%>%
  inner_join(cages,by="observed_month")%>%
  distinct() %>%
  mutate(ymon=zoo::as.yearmon(observed_month),
         .after=observed_month)

df <- eggs %>%
  inner_join(cages, by = "observed_month") %>%
  mutate(ymon = zoo::as.yearmon(observed_month),
         .after = observed_month) %>%
  select(-source.x, -source.y, -observed_month) %>%
  group_by(ymon, prod_process) %>%
  mutate(pct_hens = round(n_hens / sum(n_hens) * 100, 2),
         pct_eggs = round(n_eggs / sum(n_eggs) * 100, 2)) %>%
  ungroup() %>%
  arrange(ymon)

df%>%head

df %>%
  ggplot(aes(ymon,n_hens))+
  geom_line(aes(group=prod_type))+
  facet_wrap(~prod_process,scales = "free")

df %>%
  filter(!prod_process=="all")%>%
  ggplot()+
  geom_line(aes(ymon,n_hens,group=prod_type),
            lineend = "butt",
            arrow = arrow(length = unit(0.05,"inches"),
                          type="closed"))+  
  facet_wrap(~prod_process,scales = "free_y")+
  scale_y_log10()

df %>%
  filter(!prod_process=="all")%>%
  ggplot(aes(x=ymon))+
  geom_line(aes(y=n_hens/sum(n_hens)*100,
                group=prod_type),
            lineend = "butt",
            arrow = arrow(length = unit(0.05,"inches"),
                          type="closed"))+
  geom_line(aes(y=n_eggs/sum(n_eggs)*100,
                group=prod_type),
            lineend = "butt",
            arrow = arrow(length = unit(0.05,"inches"),
                          type="closed"))+
  facet_wrap(~prod_process,scales = "free_y")+
  scale_y_continuous(labels = scales::label_percent(decimal.mark = ",",suffix = " %"))

df %>%
  filter(!prod_process=="all")%>%
  ggplot()+
  geom_line(aes(ymon,percent_eggs,group=prod_type),
            lineend = "butt",
            arrow = arrow(length = unit(0.05,"inches"),
                          type="closed"))+  
  geom_line(aes(ymon,percent_hens,group=prod_type),
            lineend = "butt",
            arrow = arrow(length = unit(0.05,"inches"),
                          type="closed"))

Fill missing values

you can fill in the data with two approaches:

• Up - While filling the missing values, you have to specify the direction of filling of values. If you choose Up, then the filling process will be bottom-up.
• Down - In this method, you have to set the direction of filling to down.

source: https://www.digitalocean.com/community/tutorials/fill-missing-values-in-tidyr-r

Use .direction = "downup" to fill missing values in both directions

df %>%
  filter(!prod_process=="all")%>%
  tidyr::fill(percent_eggs, .direction = 'downup') %>% # View()
  mutate(percent_eggs=ifelse(is.na(percent_eggs),25,percent_eggs))%>% #View
  ggplot()+
  geom_line(aes(ymon,percent_eggs,group=prod_type),
            color="red",
            lineend = "butt",
            arrow = arrow(length = unit(0.05,"inches"),
                          type="closed"))+  
  geom_line(aes(ymon,percent_hens,group=prod_type),
            lineend = "butt",
            arrow = arrow(length = unit(0.05,"inches"),
                          type="closed"))+
  ggthemes::theme_fivethirtyeight()

Aug 2016 - Feb 2021

df %>%
  filter(!prod_process=="all")%>% # count(ymon)
  tidyr::fill(percent_eggs, .direction = 'downup') %>% # View()
  mutate(percent_eggs=ifelse(is.na(percent_eggs),25,percent_eggs))%>% #View
  pivot_longer(cols = c("percent_eggs","percent_hens"))%>%
  mutate(name=ifelse(name=="percent_eggs","eggs (%)","hens (%)")) %>%
  ggplot()+
  geom_line(aes(ymon,value,group=name,color=name),
            linewidth= 1,
            arrow = arrow(length = unit(0.1,"inches"),
                          angle = 30,
                          type="closed"))+ 
  labs(title="US Egg Production Aug 2016 - Feb 2021",
       subtitle="Hens & Eggs down/upwards",
       color="",
       caption="DataSource: #TidyTuesday Week 15 US Egg Production\n #30DayChartChallenge Day 21 down/upwards | DataViz: Federica Gazzelloni")+
  ggthemes::scale_color_fivethirtyeight()+
  ggthemes::theme_fivethirtyeight()

ggsave("w15_UEPD.png",width = 7,height = 5,bg="white")