library("dplyr")

# Student project: import and inspect the unchanged synthetic observations.
# Set the working directory to this case folder, or use run-project.R from root.
# readr imports the CSV; dplyr counts the recorded animals and groups.
data <- readr::read_csv("data.csv")

# Show the number of rows and columns, six example rows, and column types.
dim(data)
head(data, 6)
str(data)

# Count missing (NA) values in each column.
colSums(is.na(data))

# Describe the recorded values without fitting an inferential model.
summary(data)

# Count pasture groups separately from repeated group-day records.
data |> summarise(recorded_groups = n_distinct(group_id))

# Count the number of daily records from each pasture group.
data |> count(group_id)

# Next: choose a question and submit analysis-plan.qmd in Week 10.
# Create your own analysis script, using class examples for syntax where needed.