Homework 03

TidyTuesday Section (optional)

Instructions

You can count work on this week’s TidyTuesday toward the exceptional work required for an A in the Homework component.

Explore the week’s TidyTuesday challenge. Develop a research question, then answer it through a short data story with effective visualization(s). Provide sufficient background for readers to grasp your narrative.

Date: 02/17/2026 Data: Agricultural Production Statistics in New Zealand Source: Stats NZ (figure.nz)

Research Question:

Code

# Reading in the Data + loading packages
library(tidyverse)

agriculture <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2026/2026-02-17/dataset.csv')

Code

# Creating new categorical variables 

agriculture_sort <- agriculture |> 
  mutate(cows = str_detect(measure, regex("cows|heifer|calf|calves|milk|cattle|bull", ignore_case = TRUE)),
         pigs = str_detect(measure, regex("sow|pig")),
         sheep = str_detect(measure, regex("sheep|ram|ewe|lamb")),
         horses = str_detect(measure, regex("horse|stallion|foal")),
         chickens = str_detect(measure, regex("hen|chicken|egg")),
         deer = str_detect(measure, regex("deer|buck"))) |> 
  filter(cows | pigs | sheep | horses | chickens | deer)

cows_df <- agriculture_sort |> 
  filter(cows)

Code

# Visualization

agriculture_sort |> 
  filter(cows) |> 
  mutate(beef = str_detect(measure, regex("beef|Beef"))) |> 
  group_by(year_ended_june) |> 
  ggplot(aes(x = year_ended_june, y = value, color = beef, group = measure)) +
  geom_line() +
  scale_color_viridis_d() +
  labs(title = "Cattle Production Over Time: Beef and Other Production Activities", 
       subtitle = "How has beef production changed over time, relative to other cattle production activities?", 
       y = "Units Produced", 
       x = "Year", 
       color = "Beef Production", 
       alt = "This line graph reveals how beef production activities compare to other miscellaneous cattle production activities over decades. It finds that beef production activities make up a good amount of cattle production activity, though they seem to be decreasing in units produced relative to their miscellaneous counterparts.",
       caption = "Source: Stats NZ (figure.nz) | TidyTuesday W5 | Katherine Manuel")

--- title: "Homework 03" format: html: embed-resources: true --- ## TidyTuesday Section (optional) ::: {.callout-important title="Instructions"} You can count work on this week's TidyTuesday toward the exceptional work required for an A in the Homework component. ::: Explore the week's [TidyTuesday](https://github.com/rfordatascience/tidytuesday) challenge. Develop a research question, then answer it through a short data story with [effective visualization(s)]({{< var effective-viz-url >}}). Provide sufficient background for readers to grasp your narrative. Date: 02/17/2026 Data: Agricultural Production Statistics in New Zealand Source: Stats NZ (figure.nz) # Research Question: ```{r} # Reading in the Data + loading packages library(tidyverse) agriculture <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2026/2026-02-17/dataset.csv') ``` ```{r} # Creating new categorical variables agriculture_sort <- agriculture |> mutate(cows = str_detect(measure, regex("cows|heifer|calf|calves|milk|cattle|bull", ignore_case = TRUE)), pigs = str_detect(measure, regex("sow|pig")), sheep = str_detect(measure, regex("sheep|ram|ewe|lamb")), horses = str_detect(measure, regex("horse|stallion|foal")), chickens = str_detect(measure, regex("hen|chicken|egg")), deer = str_detect(measure, regex("deer|buck"))) |> filter(cows | pigs | sheep | horses | chickens | deer) cows_df <- agriculture_sort |> filter(cows) ``` ```{r} # Visualization agriculture_sort |> filter(cows) |> mutate(beef = str_detect(measure, regex("beef|Beef"))) |> group_by(year_ended_june) |> ggplot(aes(x = year_ended_june, y = value, color = beef, group = measure)) + geom_line() + scale_color_viridis_d() + labs(title = "Cattle Production Over Time: Beef and Other Production Activities", subtitle = "How has beef production changed over time, relative to other cattle production activities?", y = "Units Produced", x = "Year", color = "Beef Production", alt = "This line graph reveals how beef production activities compare to other miscellaneous cattle production activities over decades. It finds that beef production activities make up a good amount of cattle production activity, though they seem to be decreasing in units produced relative to their miscellaneous counterparts.", caption = "Source: Stats NZ (figure.nz) | TidyTuesday W5 | Katherine Manuel") ```