Psi Chi R - Jan 2025

Hello! Welcome to January’s contest. In honor of National Cheese Day (January 20th) we’ll be looking into some award winning cheeses! This month, we’ll also test out learning a new skill (for you, and ME!) - making maps! One of the tasks for this month will be to map out winning cheeses. Please note, this is one of my first attempts at making maps in R so it is not by any means fancy, but, I feel it is important for all of us to try learning new things :)

https://osf.io/2hgzs/wiki/home/

knitr::opts_chunk$set(echo = T,message = F,warning = F)

#setwd("C:/Users/alanh/Documents/R/Psi_Chi_R")

setwd("~/R/Psi_Chi_R")

library(tidyverse)

data=read_csv('data.csv')

sum_rows = function(x){
  x %>% 
    ungroup() %>% 
    bind_rows(summarise(.,across(where(is.numeric),sum,na.rm=T)))
}

sum_cols = function(x){
  x %>% 
    mutate(Total = rowSums(across(where(is.numeric)), na.rm =T))
}

#EDA

names(data) = make.names(colnames(data))

SmartEDA::ExpData(data,type=2)

Level 1.

Remove any rows where ‘company,’ ‘product_name,’ and/or ‘rating’ are blank.

data1 = data %>% 
  filter(!is.na(company),
         !is.na(product_name),
         !is.na(rating))

Level 2.

Make one table that shows the counts of each category within ‘rating,’ and then make a second table showing counts for each ‘country.’

data1 %>% 
  group_by(rating) %>% 
  count() %>% 
  arrange(desc(n))

data1 %>% 
  group_by(country) %>% 
  count() %>% 
  arrange(desc(n))

Level 3.

First, make a table showing how many of each medal type (rating) each cheese (Category_Corrected).

data1 %>% 
  group_by(rating,Category.Corrected)

Which cheese has the most “Super Golds?” Next, modify the table and indicate which country produced the most “Super Gold” cheeses.

5004 - Hard goats’ milk cheese plain Spain

data1 %>% 
  group_by(Category.Corrected,rating,country) %>% 
  count() %>% 
  arrange(desc(n)) %>% 
  filter(rating=='SUPER GOLD')

Level 4.

Generate a map that shows which countries have won super gold medals. Since this is a more advanced skill, I’ve provided a starter code below

data1 %>% 
  filter(rating=='SUPER GOLD') %>% 
  ggplot(aes(y=(fct_infreq(country))))+
  geom_bar()+
  labs(x='Super Gold Medals',
       title='Super Gold Medals by Country')+
  theme(plot.title = element_text(hjust = .5))