Functions in R and your first scraper

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.title[
# Functions in R and your first scraper
]
.author[
### Will Ju
]

---

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# Scraping with CSS

---

# Scrape the data

Use the `rvest` package to download and parse data tables for Hall of Fame voting records.

```r
url <- "https://www.baseball-reference.com/awards/hof_2025.shtml"

library(rvest)
site <- read_html(url)
```

The command `html_element` allows us to select based on css selectors (www3 school CSS)[https://www.w3schools.com/CSSref/css_selectors.php] or (CSS Diner)[https://flukeout.github.io/]

Load the baseball reference website in Chrome. Then use View > Developer > Inspect Elements.

What id should we use?

---

# BBWAA Table

table has id `hof_BBWAA`:

```r
site %>% html_element(css="#hof_BBWAA") %>% html_table() %>% head(3)
```

```
## # A tibble: 3 × 39
##   ``    ``           ``    ``    ``    ``    ``    ``    ``    ``    ``    ``   
##   <chr> <chr>        <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 Rk    Name         YoB   Votes %vote HOFm  HOFs  Yrs   WAR   WAR7  JAWS  Jpos 
## 2 1     Ichiro Suzu… 1st   393   99.7% 235   44    19    60.0  43.7  51.8  56.0 
## 3 2     CC Sabathia  1st   342   86.8% 128   48    19    62.3  39.4  50.8  61.3 
## # ℹ 27 more variables: `Batting Stats` <chr>, `Batting Stats` <chr>,
## #   `Batting Stats` <chr>, `Batting Stats` <chr>, `Batting Stats` <chr>,
## #   `Batting Stats` <chr>, `Batting Stats` <chr>, `Batting Stats` <chr>,
## #   `Batting Stats` <chr>, `Batting Stats` <chr>, `Batting Stats` <chr>,
## #   `Batting Stats` <chr>, `Batting Stats` <chr>, `Pitching Stats` <chr>,
## #   `Pitching Stats` <chr>, `Pitching Stats` <chr>, `Pitching Stats` <chr>,
## #   `Pitching Stats` <chr>, `Pitching Stats` <chr>, `Pitching Stats` <chr>, …
```

---

# Reset the column names from the first row

```r
bbwaa <- site %>% html_element(css="#hof_BBWAA") %>% html_table() 
colnames(bbwaa) <- bbwaa[1,]
bbwaa <- bbwaa[-1,]
head(bbwaa)
```

```
## # A tibble: 6 × 39
##   Rk    Name       YoB   Votes `%vote` HOFm  HOFs  Yrs   WAR   WAR7  JAWS  Jpos 
##   <chr> <chr>      <chr> <chr> <chr>   <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 1     Ichiro Su… 1st   393   99.7%   235   44    19    60.0  43.7  51.8  56.0 
## 2 2     CC Sabath… 1st   342   86.8%   128   48    19    62.3  39.4  50.8  61.3 
## 3 3     Billy Wag… 10th  325   82.5%   107   24    16    27.7  19.8  23.7  31.6 
## 4 4     Carlos Be… 3rd   277   70.3%   126   52    20    70.0  44.4  57.2  58.0 
## 5 5     Andruw Jo… 8th   261   66.2%   109   34    17    62.7  46.4  54.6  58.0 
## 6 6     Chase Utl… 2nd   157   39.8%   94    36    16    64.6  49.3  57.0  56.9 
## # ℹ 27 more variables: G <chr>, AB <chr>, R <chr>, H <chr>, HR <chr>,
## #   RBI <chr>, SB <chr>, BB <chr>, BA <chr>, OBP <chr>, SLG <chr>, OPS <chr>,
## #   `OPS+` <chr>, W <chr>, L <chr>, ERA <chr>, `ERA+` <chr>, WHIP <chr>,
## #   G <chr>, GS <chr>, SV <chr>, IP <chr>, H <chr>, HR <chr>, BB <chr>,
## #   SO <chr>, `Pos Summary` <chr>
```

---
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# Functions in R

---

# Functions in R

- Have been using functions a lot, now we want to write them ourselves!

- Idea: avoid repetitive coding (errors will creep in)

- Instead: extract common core, wrap it in a function, make it reusable

---

# Structure of functions

- Name

- Input arguments

- names,

- default values

- Body

- Output values

---

# A first function

```r
mymean <- function(x) {
	return(sum(x)/length(x))
}
```

```r
mymean(1:15)
```

```
## [1] 8
```

```r
mymean(c(1:15, NA))
```

```
## [1] NA
```

---

# A first function (2)

```r
mymean <- function(x, na.rm=F) {
	if (na.rm) x <- na.omit(x)
	
	return(sum(x)/length(x))
}

mymean(1:15)
```

```
## [1] 8
```

```r
mymean(c(1:15, NA), na.rm=T)
```

```
## [1] 8
```

---
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# Your Turn: a scraper

The package `rvest` allows us to download data from the baseball reference website `url` using the following lines of code:

```r
library(rvest)
site <- read_html(url)
bbwaa <- site %>% html_element("#hof_BBWAA") %>% html_table()
```

Write a function that uses the url as input argument, scrapes the data and returns it

Try out your function on the site
https://www.baseball-reference.com/awards/hof_2024.shtml

---

# Your turn - solution

```r
library(rvest)

bbwaa_scraper <- function(url) {
  site <- read_html(url)
  bbwaa <- site %>% html_element("#hof_BBWAA") %>% html_table()
  
  bbwaa
}

bbwaa_scraper("https://www.baseball-reference.com/awards/hof_2024.shtml")
```

```
## # A tibble: 27 × 39
##    ``    ``          ``    ``    ``    ``    ``    ``    ``    ``    ``    ``   
##    <chr> <chr>       <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
##  1 Rk    Name        YoB   Votes %vote HOFm  HOFs  Yrs   WAR   WAR7  JAWS  Jpos 
##  2 1     Adrian Bel… 1st   366   95.1% 163   55    21    93.7  48.9  71.3  56.1 
##  3 2     Todd Helton 6th   307   79.7% 175   59    17    61.8  46.6  54.2  53.5 
##  4 3     Joe Mauer   1st   293   76.1% 92    41    15    55.6  39.1  47.4  44.3 
##  5 4     Billy Wagn… 9th   284   73.8% 107   24    16    27.7  19.8  23.7  31.6 
##  6 5     X-Gary She… 10th  246   63.9% 158   61    22    60.5  38.0  49.3  56.0 
##  7 6     Andruw Jon… 7th   237   61.6% 109   34    17    62.7  46.4  54.6  58.0 
##  8 7     Carlos Bel… 2nd   220   57.1% 126   52    20    70.0  44.4  57.2  58.0 
##  9 8     Alex Rodri… 3rd   134   34.8% 390   77    22    117.4 64.3  90.8  55.4 
## 10 9     Manny Rami… 8th   125   32.5% 226   69    19    69.3  39.9  54.6  53.5 
## # ℹ 17 more rows
## # ℹ 27 more variables: `Batting Stats` <chr>, `Batting Stats` <chr>,
## #   `Batting Stats` <chr>, `Batting Stats` <chr>, `Batting Stats` <chr>,
## #   `Batting Stats` <chr>, `Batting Stats` <chr>, `Batting Stats` <chr>,
## #   `Batting Stats` <chr>, `Batting Stats` <chr>, `Batting Stats` <chr>,
## #   `Batting Stats` <chr>, `Batting Stats` <chr>, `Pitching Stats` <chr>,
## #   `Pitching Stats` <chr>, `Pitching Stats` <chr>, `Pitching Stats` <chr>, …
```

---
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# Your Turn: expanding

Expand your function by a parameter `element` that enables you to download different pieces from a website.

Set `element` to "#hof_Veterans" and try out your function for the year 2025.

---
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# Always scrape data responsibly!