parsons.Rmd

---
title: "Parsons"
output: learnr::tutorial
runtime: shiny_prerendered
---

```{r setup, include=FALSE}
library(learnr)
library(parsons)
library(gsheet)
library(dplyr)
library(ggplot2)
knitr::opts_chunk$set(echo = FALSE)
```



## Creating a parsons question

### Using pass and fail conditions

An alternative way to specify the correct answer(s) is to supply a pass_if() statment. Using `pass_if` and `fail_if` is a powerful way to provide feedback to your students.

These `pass_if` and `fail_if` statements are evaluated in turn, until the first expectation evaluates to `TRUE`, and the `learnr` will provide the feedback in the `message`.

You can specify `pass_if()` as well as `fail_if()` in any of the following ways:   
- A character vector, that must be matched exatcly, or   
- A function in the tradition form `function(x)...`, e.g. `function(x) length(x) <3`   
- A function specified using the `rlang` tidy evaluation formula notation, e.g. `~length(.) < 3`

### Features

- For tidyverse problem_type, items (except the last) in the right hand column will have a %>%  appended, and for ggplot2 every line will be followed by a +.    
- The initial values are shuffled into random answer order.

### Limitations

- it does not do any code evaluation   
- it does not support identation   
- it assumes code is from the tidyverse and only supports the magrittr pipe ( %>% ) operator   

## Quiz 1


**What are the top 5 Sub.Category measured by sum profit?**  

```{r}
retail <- read.csv("data_input/retail.csv")
```

Try to execute your solution here:
```{r addition, exercise=TRUE, exercise.eval = TRUE}
head(retail)
```

```{r quiz1}
question_parsons(
  initial = c(
    "Accessories",
    "Copiers",
    "Binders",
    "Phones",
    "Paper"
  ),
  answer(
    c(
      "Copiers",
      "Phones",
      "Accessories",
      "Paper",
      "Binders"
    ),
    correct = TRUE
  ),
  fail_if(
    ~ length(.) < 5,
    "Provide more answer"
  ),
  submit_button = "submit answer"
)
```


## Quiz 2

*Which category product makes up our high-value profit*

```{r quiz2}
question_parsons(
  initial = c(
    "group_by(Category)",
    "retail",
    "arrange(desc(total_profit))",
    "summarise(total_profit = sum(Profit))"
  ),
  answer(
    c(
      "retail",
      "group_by(Category)",
      "summarise(total_profit = sum(Profit))",
     "arrange(desc(total_profit))"
    ),
    correct = TRUE
  ),
  fail_if(
    ~ length(.) < 4,
    "Provide more answer"
  ),
  fail_if(
    ~{.[1] != "retail"},
    message = "your solution should start with 'retail'"
  ),
  fail_if(
    ~{.[2] != "group_by(Category"},
    message = "you need to group_by first, before summarise"
  )
  ,
  submit_button = "submit answer",
  problem_type = "tidyverse",
  allow_retry = TRUE
)
```




## Quiz 3

How to create this plot? (use `retail2` dataset)


```{r}
retail2 <- retail[1:100,]
ggplot(retail2,aes(x = Category, y = Sales)) +
  geom_boxplot() + geom_jitter() 
```

Try to execute your solution here:
```{r addition2, exercise=TRUE, exercise.eval = TRUE}
retail2 <- retail[1:100,]
```


```{r quiz}
question_parsons(
  initial = c(
    "geom_boxplot()",
    "geom_jitter() ",
    "ggplot(retail2,aes(x = Category, y = Sales))"
  ),
  pass_if(
    c(
    "ggplot(retail2,aes(x = Category, y = Sales))",
    "geom_boxplot()",
      "geom_jitter() "
    )
  ),submit_button = "submit answer",
  problem_type = "ggplot2"
)
```