```{r include=FALSE}
knitr::opts_chunk$set(
  fig.width = 6,
  fig.height = 4,
  fig.align = "center",
  out.width = "100%",
  code.line.numbers = FALSE,
  fig.retina = 4,
  echo = TRUE,
  message = FALSE,
  warning = FALSE,
  error = FALSE,
  cache = FALSE,
  dev.args = list(pointsize = 11)
)
```

## 🎯 Objectives

The goal of this worksheet is to search for R packages that can be used for exploring data, and to understand their capacity. 

The paper [The Landscape of R Packages for Automated Exploratory Data Analysis](https://journal.r-project.org/articles/RJ-2019-033/)


## 🧩 Tasks 

#### 1. Use AI to obtain a list of packages that might be used for exploring data in R.

::: unilur-solution
Here is my list of prompts:

- Do you know the paper "The Landscape of R Packages for Automated Exploratory Data Analysis" ?
- What would you recommend for R packages for exploratory data analysis today? I'm not sure that the package list in that paper are reasonable 5 years into the future of today.
- What about databot? (Notice the botching of author: "Jennifer (Yihui) Cheng and others")
- Are there any packages that are true to Tukey's original book Exploratory Data Analysis from 1977?
- What about packages that can explore high-dimensional data?


:::

#### 2. Pick one of the packages mentioned and give it a spin

::: unilur-solution
:::

#### 3. Use AI to learn about some of Tukey's most famous quotes, and also what methods he developed are still in common use today

::: unilur-solution

My prompts:

- What are some of Tukey's most famous quotes?
- What are some methods that Tukey developed that are commonly used today?
- What are the R packages that have these methods?
- What about the letter value plot?
- I would love a "A one-page “Tukey contributions” teaching sheet for a lecture?" Can you provide it as a quarto document?

:::

#### 4. For the gardenR example from week 1, ask for some Tukey-style summaries of this data

::: unilur-solution

Prompt:

- For the gardenR package data, could you make some code to do Tukey-like summaries of the data?


:::
