## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----setup--------------------------------------------------------------------
knitr::opts_chunk$set(warning = FALSE, message = FALSE)
library(ausOpenData)
library(ggplot2)
library(dplyr)

## ----aus-list-datasets--------------------------------------------------------
aus_list_datasets() |> head()

## ----aus-vacant-pull----------------------------------------------------------
aus_golf_courses <- aus_pull_dataset(
  dataset = "dtkn-v97q", limit = 2, timeout_sec = 90)

aus_golf_courses <- aus_pull_dataset(
  dataset = "golf_courses_in_austin", limit = 2, timeout_sec = 90)

## ----filter-routine-----------------------------------------------------------

aus_routine_results <- aus_pull_dataset(dataset = "ecmv-9xxi",limit = 3, timeout_sec = 90, filters = list(process_description = "Routine Inspection"))

aus_routine_results

# Checking to see the filtering worked
aus_routine_results |>
  distinct(process_description)

## ----filter-aus-hundreds------------------------------------------------------
# Creating the dataset
aus_routine_100 <- aus_pull_dataset(dataset = "ecmv-9xxi", limit = 50, timeout_sec = 90, filters = list(process_description = "Routine Inspection", score = 100))

# Calling head of our new dataset
aus_routine_100 |>
  slice_head(n = 6)

# Quick check to make sure our filtering worked
aus_routine_100 |>
  summarize(rows = n())

aus_routine_100 |>
  distinct(process_description)

aus_routine_100 |>
  distinct(score)