wrangle.qmd

---
title: "Wrangle Data with {dplyr}"
date-modified: 'today'
date-format: long

license: CC BY-NC  
bibliography: references.bib
---

{[`dplyr`](https://dplyr.tidyverse.org)} verbs help you wrangle, clean, and normalize your data

::: column-margin
```{=html}
<iframe width="300" height="200" src="https://www.youtube.com/embed/PGSXf-NMWVg" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
```
:::

| dplyr function | use for                                    |
|----------------|--------------------------------------------|
| `select()`     | subset columns                             |
| `filter()`     | subset rows                                |
| `arrange()`    | sort rows by column variable values        |
| `mutate()`     | Create new, or modify variables            |
| `group_by()`   | use with summarize for subtotals           |
| `summarize()`  | generate column totals and subtotals, etc. |
| `count()`      | a specialized `summarize()` function       |

### Examples

First we need to load the {dplyr} package for wrangling and the {readr} package for importing CSV data. In our case, we'll do that by loading the tidyverse which loads {dplyr}, {readr} and several other helpful packages. Then we need to load our data

```{r}
#| warning: false
#| message: false

library(tidyverse)
brodhead_center <- read_csv("data/brodhead_center.csv")
```

#### `select()`

```{r}
brodhead_center |> 
  select(name, type)
```

::: column-margin
[![Select columns](images/select.svg){fig-alt="Select columns"}](https://dplyr.tidyverse.org/reference/select.html)
:::

#### `filter()`

```{r}
brodhead_center |> 
  filter(menuType == "dessert")
```

::: column-margin
[![Filter by rows](images/filter_by_rows.svg){fig-alt="Filter by rows"}](https://dplyr.tidyverse.org/reference/filter.html)
:::

#### `arrange()`

```{r}
brodhead_center |> 
  arrange(cost)
```

::: column-margin
[![Arrange rows by the values in a column](images/arrange_rows.svg){fig-alt="Arrange rows by the values in a column"}](https://dplyr.tidyverse.org/reference/arrange.html)
:::

#### `mutate()`

```{r}
brodhead_center |> 
  mutate(ratings_high = rating * 2)
```

::: column-margin
[![Create new variable or modify variable with mutate()](images/mutate.svg){fig-alt="Create new variable or modify variable with mutate()"}](https://dplyr.tidyverse.org/reference/mutate.html)
:::

We can also mutate data by groups or categories

```{r}
brodhead_center |> 
  mutate(avg_item_rating_rest = mean(rating, na.rm = TRUE), 
         .by = name, 
         .after = name)
```

#### `count()`

```{r}
#| label: margin-picture-count
#| echo: false
#| column: margin

brodhead_center |> 
  count(menuType) |> 
  arrange(desc(n)) |> 
  gt::gt() |> 
  gt::tab_header(title = "Count values in a group")
```

```{r}
brodhead_center |> 
  count(menuType)
```

#### `group_by()` & `summarise()`

```{r}
#| label: margin-picture-summarize
#| echo: false
#| column: margin

brodhead_center |> 
  summarise(Sum_of_cost = sum(cost)) |> 
  gt::gt() |> 
  gt::tab_header(title = "Summarise column")
```

```{r}
brodhead_center |> 
  group_by(name) |> 
  summarise(min_cost = min(cost), mean_cost = mean(cost), max_cost = max(cost))
```

##### or

Summarize by groups, without `group_by()`

```{r}
brodhead_center |> 
  summarise(min_cost = min(cost), .by = name)
```