Using R for Your Big Data Cup Project

class: inverse, center, middle

# Using R for Your Big Data Cup Project
<img src="figs/hanic/puck.png" width="250px"/>
### A gentle intro and some tips & tricks
Meghan Hall <br> <i class="fab  fa-twitter "></i> [@MeghanMHall](https://www.twitter.com/MeghanMHall) <br> [meghan.rbind.io](https://meghan.rbind.io/) <br> [Hockey (Analytics) Night in Canada](https://www.hanic-analytics.com) <br> Feb. 18, 2021

---
background-image: url(figs/hanic/puck.png)
background-position: 98% 2%
background-size: 114px 104px
padding-right: 10px
layout: true
---

## Can I teach you R in 10 minutes?

...no &nbsp; 😞

But we *can*...

- talk about what's easier to do in R
- go over some common functions you might use for this project
- discuss a roadmap for learning more

<br>

**Disclaimer** <br>
*The speaker herein pledges as follows: no declarative statements will be uttered about how R is objectively "the best" and no moral judgments will be made on which software, IDE, programming language, packages, dark mode, etc. the viewer chooses to use and/or not use.*

**tl;dr** <br>
I don't care what you use for your project! Use Excel! Use Python! Use SAS! Use an abacus!

<br>

But these are my 10 minutes, so we're going to talk about R.

---

## Step 0: How does one use R, exactly?

1️⃣ &nbsp; the language itself: [https://cloud.r-project.org/](https://cloud.r-project.org/)

<br>

2️⃣ &nbsp; the IDE (integrated development environment): [https://rstudio.com/products/rstudio/download/](https://rstudio.com/products/rstudio/download/)

---

## Step 1: Data!

```r
library(tidyverse)
library(janitor)

scouting <- read_csv("https://tinyurl.com/BDCscouting") %>% 
  clean_names()

nwhl <- read_csv("https://tinyurl.com/BDCnwhl") %>% 
  clean_names()

women <- read_csv("https://tinyurl.com/BDCwomens") %>% 
  clean_names()
```

---

## Step 1: Data!

```r
*library(tidyverse)
library(janitor)

scouting <- read_csv("https://tinyurl.com/BDCscouting") %>%
  clean_names()

nwhl <- read_csv("https://tinyurl.com/BDCnwhl") %>%
  clean_names()

women <- read_csv("https://tinyurl.com/BDCwomens") %>%
  clean_names()
```

---

## Step 1: Data!

```r
library(tidyverse) 
library(janitor)

*scouting <- read_csv("https://tinyurl.com/BDCscouting") %>%
  clean_names()

*nwhl <- read_csv("https://tinyurl.com/BDCnwhl") %>%
  clean_names()

*women <- read_csv("https://tinyurl.com/BDCwomens") %>%
  clean_names() 
```

---

## Step 1: Data!

```r
library(tidyverse) 
*library(janitor)

scouting <- read_csv("https://tinyurl.com/BDCscouting") %>%
* clean_names()

nwhl <- read_csv("https://tinyurl.com/BDCnwhl") %>% 
* clean_names()

women <- read_csv("https://tinyurl.com/BDCwomens") %>% 
* clean_names()
```

---

## Step 2: Explore

```r
*View(scouting)

*scouting %>%
* glimpse()

scouting %>% 
  count(event)

scouting %>% 
  count(event, detail_1)
```

---

## Step 2: Explore

```r
View(scouting)

scouting %>%
  glimpse()

*scouting %>%
* count(event)

scouting %>% 
  count(event, detail_1)
```

---

## Step 2: Explore

```r
View(scouting)

scouting %>%
  glimpse()

scouting %>%
  count(event)

*scouting %>%
* count(event, detail_1)
```

---

## Step 3: A Question

From the `scouting` data, among players who've taken at least 50 faceoffs, who has the best faceoff percentage?

(Is this the most *rigorous* Big Data Cup question? No, but I only have 10 minutes!)

<table class="table" style="font-size: 14px; width: auto !important; ">
 <thead>
  <tr>
   <th style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> game_date </th>
   <th style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> team </th>
   <th style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> player </th>
   <th style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> event </th>
   <th style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> player_2 </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Sudbury Wolves </td>
   <td style="text-align:left;"> Blake Murray </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Connor Lockhart </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Sudbury Wolves </td>
   <td style="text-align:left;"> Macauley Carson </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Austen Swankler </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Sudbury Wolves </td>
   <td style="text-align:left;"> Quinton Byfield </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Chad Yetman </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Sudbury Wolves </td>
   <td style="text-align:left;"> Macauley Carson </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Austen Swankler </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Sudbury Wolves </td>
   <td style="text-align:left;"> Quinton Byfield </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Chad Yetman </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Erie Otters </td>
   <td style="text-align:left;"> Alex Gritz </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Blake Murray </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Erie Otters </td>
   <td style="text-align:left;"> Connor Lockhart </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Ethan Larmand </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Erie Otters </td>
   <td style="text-align:left;"> Austen Swankler </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Macauley Carson </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Erie Otters </td>
   <td style="text-align:left;"> Chad Yetman </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Quinton Byfield </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Erie Otters </td>
   <td style="text-align:left;"> Brendan Hoffmann </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Blake Murray </td>
  </tr>
</tbody>
</table>

---

## Step 3: A Question

From the `scouting` data, among players who've taken at least 50 faceoffs, who has the best faceoff percentage?

(Is this the most *rigorous* Big Data Cup question? No, but I only have 10 minutes!)

<table class="table" style="font-size: 14px; width: auto !important; ">
 <thead>
  <tr>
   <th style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> game_date </th>
   <th style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> team </th>
   <th style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> player </th>
   <th style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> event </th>
   <th style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> player_2 </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Sudbury Wolves </td>
   <td style="text-align:left;"> Blake Murray </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Connor Lockhart </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Sudbury Wolves </td>
   <td style="text-align:left;"> Macauley Carson </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Austen Swankler </td>
  </tr>
  <tr>
   <td style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> 2019-09-20 </td>
   <td style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> Sudbury Wolves </td>
   <td style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> Quinton Byfield </td>
   <td style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> Faceoff Win </td>
   <td style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> Chad Yetman </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Sudbury Wolves </td>
   <td style="text-align:left;"> Macauley Carson </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Austen Swankler </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Sudbury Wolves </td>
   <td style="text-align:left;"> Quinton Byfield </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Chad Yetman </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Erie Otters </td>
   <td style="text-align:left;"> Alex Gritz </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Blake Murray </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Erie Otters </td>
   <td style="text-align:left;"> Connor Lockhart </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Ethan Larmand </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Erie Otters </td>
   <td style="text-align:left;"> Austen Swankler </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Macauley Carson </td>
  </tr>
  <tr>
   <td style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> 2019-09-20 </td>
   <td style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> Erie Otters </td>
   <td style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> Chad Yetman </td>
   <td style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> Faceoff Win </td>
   <td style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> Quinton Byfield </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 2019-09-20 </td>
   <td style="text-align:left;"> Erie Otters </td>
   <td style="text-align:left;"> Brendan Hoffmann </td>
   <td style="text-align:left;"> Faceoff Win </td>
   <td style="text-align:left;"> Blake Murray </td>
  </tr>
</tbody>
</table>

---

## Step 3: A Question

<table class="table" style="font-size: 14px; width: auto !important; ">
 <thead>
  <tr>
   <th style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> player </th>
   <th style="text-align:right;font-weight: bold;color: white !important;background-color: #5C164E !important;"> faceoffs </th>
   <th style="text-align:right;font-weight: bold;color: white !important;background-color: #5C164E !important;"> faceoff_wins </th>
   <th style="text-align:right;font-weight: bold;color: white !important;background-color: #5C164E !important;"> faceoff_perc </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Ty Dellandrea </td>
   <td style="text-align:right;"> 55 </td>
   <td style="text-align:right;"> 35 </td>
   <td style="text-align:right;"> 0.6363636 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Cole Schwindt </td>
   <td style="text-align:right;"> 57 </td>
   <td style="text-align:right;"> 36 </td>
   <td style="text-align:right;"> 0.6315789 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Cam Hillis </td>
   <td style="text-align:right;"> 104 </td>
   <td style="text-align:right;"> 64 </td>
   <td style="text-align:right;"> 0.6153846 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Lucas Theriault </td>
   <td style="text-align:right;"> 52 </td>
   <td style="text-align:right;"> 29 </td>
   <td style="text-align:right;"> 0.5576923 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Keean Washkurak </td>
   <td style="text-align:right;"> 55 </td>
   <td style="text-align:right;"> 29 </td>
   <td style="text-align:right;"> 0.5272727 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Danny Zhilkin </td>
   <td style="text-align:right;"> 67 </td>
   <td style="text-align:right;"> 34 </td>
   <td style="text-align:right;"> 0.5074627 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Austen Swankler </td>
   <td style="text-align:right;"> 334 </td>
   <td style="text-align:right;"> 169 </td>
   <td style="text-align:right;"> 0.5059880 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Ryan McGregor </td>
   <td style="text-align:right;"> 72 </td>
   <td style="text-align:right;"> 36 </td>
   <td style="text-align:right;"> 0.5000000 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Hayden Fowler </td>
   <td style="text-align:right;"> 310 </td>
   <td style="text-align:right;"> 149 </td>
   <td style="text-align:right;"> 0.4806452 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Chad Yetman </td>
   <td style="text-align:right;"> 724 </td>
   <td style="text-align:right;"> 343 </td>
   <td style="text-align:right;"> 0.4737569 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Connor Lockhart </td>
   <td style="text-align:right;"> 207 </td>
   <td style="text-align:right;"> 92 </td>
   <td style="text-align:right;"> 0.4444444 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Noah Sedore </td>
   <td style="text-align:right;"> 68 </td>
   <td style="text-align:right;"> 30 </td>
   <td style="text-align:right;"> 0.4411765 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Brendan Hoffmann </td>
   <td style="text-align:right;"> 488 </td>
   <td style="text-align:right;"> 197 </td>
   <td style="text-align:right;"> 0.4036885 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Elias Cohen </td>
   <td style="text-align:right;"> 149 </td>
   <td style="text-align:right;"> 57 </td>
   <td style="text-align:right;"> 0.3825503 </td>
  </tr>
</tbody>
</table>

---

## Step 3: A Question

```r
faceoffs <- scouting %>% 
  filter(event == "Faceoff Win") %>% 
  select(player, player_2) %>% 
  rename(winner = player,
         loser = player_2) %>% 
  pivot_longer(winner:loser, 
               names_to = "status", 
               values_to = "player") %>% 
  mutate(win = ifelse(status == "winner", 1, 0)) %>% 
  group_by(player) %>% 
  summarize(faceoffs = n(),
            faceoff_wins = sum(win)) %>% 
  mutate(faceoff_perc = faceoff_wins / faceoffs) %>% 
  filter(faceoffs >= 50) %>% 
  arrange(desc(faceoff_perc))
```

---

## Step 3: A Question

```r
*faceoffs <- scouting %>%
  filter(event == "Faceoff Win") %>% 
  select(player, player_2) %>% 
  rename(winner = player,
         loser = player_2) %>% 
  pivot_longer(winner:loser, 
               names_to = "status", 
               values_to = "player") %>% 
  mutate(win = ifelse(status == "winner", 1, 0)) %>% 
  group_by(player) %>% 
  summarize(faceoffs = n(),
            faceoff_wins = sum(win)) %>% 
  mutate(faceoff_perc = faceoff_wins / faceoffs) %>% 
  filter(faceoffs >= 50) %>% 
  arrange(desc(faceoff_perc))
```

---

## Step 3: A Question

```r
faceoffs <- scouting %>% 
* filter(event == "Faceoff Win") %>%
* select(player, player_2) %>%
  rename(winner = player,
         loser = player_2) %>% 
  pivot_longer(winner:loser, 
               names_to = "status", 
               values_to = "player") %>% 
  mutate(win = ifelse(status == "winner", 1, 0)) %>% 
  group_by(player) %>% 
  summarize(faceoffs = n(),
            faceoff_wins = sum(win)) %>% 
  mutate(faceoff_perc = faceoff_wins / faceoffs) %>% 
  filter(faceoffs >= 50) %>% 
  arrange(desc(faceoff_perc))
```

---

## Step 3: A Question

```r
faceoffs <- scouting %>% 
  filter(event == "Faceoff Win") %>% 
  select(player, player_2) %>% 
* rename(winner = player,
*        loser = player_2) %>%
  pivot_longer(winner:loser, 
               names_to = "status", 
               values_to = "player") %>% 
  mutate(win = ifelse(status == "winner", 1, 0)) %>% 
  group_by(player) %>% 
  summarize(faceoffs = n(),
            faceoff_wins = sum(win)) %>% 
  mutate(faceoff_perc = faceoff_wins / faceoffs) %>% 
  filter(faceoffs >= 50) %>% 
  arrange(desc(faceoff_perc))
```

---

## Step 3: A Question

```r
faceoffs <- scouting %>% 
  filter(event == "Faceoff Win") %>% 
  select(player, player_2) %>% 
  rename(winner = player,
         loser = player_2) %>% 
* pivot_longer(winner:loser,
*              names_to = "status",
*              values_to = "player") %>%
  mutate(win = ifelse(status == "winner", 1, 0)) %>% 
  group_by(player) %>% 
  summarize(faceoffs = n(),
            faceoff_wins = sum(win)) %>% 
  mutate(faceoff_perc = faceoff_wins / faceoffs) %>% 
  filter(faceoffs >= 50) %>% 
  arrange(desc(faceoff_perc))
```

---

## Step 3: A Question

---

## Step 3: A Question

```r
faceoffs <- scouting %>% 
  filter(event == "Faceoff Win") %>% 
  select(player, player_2) %>%
  rename(winner = player,
         loser = player_2) %>% 
  pivot_longer(winner:loser, 
               names_to = "status", 
               values_to = "player") %>% 
* mutate(win = ifelse(status == "winner", 1, 0)) %>%
  group_by(player) %>% 
  summarize(faceoffs = n(),
            faceoff_wins = sum(win)) %>% 
  mutate(faceoff_perc = faceoff_wins / faceoffs) %>% 
  filter(faceoffs >= 50) %>% 
  arrange(desc(faceoff_perc))
```

---

## Step 3: A Question

```r
faceoffs <- scouting %>% 
  filter(event == "Faceoff Win") %>% 
  select(player, player_2) %>% 
  rename(winner = player,
         loser = player_2) %>% 
  pivot_longer(winner:loser, 
               names_to = "status", 
               values_to = "player") %>% 
  mutate(win = ifelse(status == "winner", 1, 0)) %>% 
* group_by(player) %>%
* summarize(faceoffs = n(),
*           faceoff_wins = sum(win)) %>%
  mutate(faceoff_perc = faceoff_wins / faceoffs) %>% 
  filter(faceoffs >= 50) %>% 
  arrange(desc(faceoff_perc))
```

---

## Step 3: A Question

```r
faceoffs <- scouting %>% 
  filter(event == "Faceoff Win") %>% 
  select(player, player_2) %>% 
  rename(winner = player,
         loser = player_2) %>% 
  pivot_longer(winner:loser, 
               names_to = "status", 
               values_to = "player") %>% 
  mutate(win = ifelse(status == "winner", 1, 0)) %>% 
  group_by(player) %>% 
  summarize(faceoffs = n(),
            faceoff_wins = sum(win)) %>% 
* mutate(faceoff_perc = faceoff_wins / faceoffs) %>%
* filter(faceoffs >= 50) %>%
  arrange(desc(faceoff_perc))
```

---

## Step 3: A Question

---

## Step 3: A Question

<table class="table" style="font-size: 14px; width: auto !important; ">
 <thead>
  <tr>
   <th style="text-align:left;font-weight: bold;color: white !important;background-color: #5C164E !important;"> player </th>
   <th style="text-align:right;font-weight: bold;color: white !important;background-color: #5C164E !important;"> faceoffs </th>
   <th style="text-align:right;font-weight: bold;color: white !important;background-color: #5C164E !important;"> faceoff_wins </th>
   <th style="text-align:right;font-weight: bold;color: white !important;background-color: #5C164E !important;"> faceoff_perc </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Ty Dellandrea </td>
   <td style="text-align:right;"> 55 </td>
   <td style="text-align:right;"> 35 </td>
   <td style="text-align:right;"> 0.6363636 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Cole Schwindt </td>
   <td style="text-align:right;"> 57 </td>
   <td style="text-align:right;"> 36 </td>
   <td style="text-align:right;"> 0.6315789 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Cam Hillis </td>
   <td style="text-align:right;"> 104 </td>
   <td style="text-align:right;"> 64 </td>
   <td style="text-align:right;"> 0.6153846 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Lucas Theriault </td>
   <td style="text-align:right;"> 52 </td>
   <td style="text-align:right;"> 29 </td>
   <td style="text-align:right;"> 0.5576923 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Keean Washkurak </td>
   <td style="text-align:right;"> 55 </td>
   <td style="text-align:right;"> 29 </td>
   <td style="text-align:right;"> 0.5272727 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Danny Zhilkin </td>
   <td style="text-align:right;"> 67 </td>
   <td style="text-align:right;"> 34 </td>
   <td style="text-align:right;"> 0.5074627 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Austen Swankler </td>
   <td style="text-align:right;"> 334 </td>
   <td style="text-align:right;"> 169 </td>
   <td style="text-align:right;"> 0.5059880 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Ryan McGregor </td>
   <td style="text-align:right;"> 72 </td>
   <td style="text-align:right;"> 36 </td>
   <td style="text-align:right;"> 0.5000000 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Hayden Fowler </td>
   <td style="text-align:right;"> 310 </td>
   <td style="text-align:right;"> 149 </td>
   <td style="text-align:right;"> 0.4806452 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Chad Yetman </td>
   <td style="text-align:right;"> 724 </td>
   <td style="text-align:right;"> 343 </td>
   <td style="text-align:right;"> 0.4737569 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Connor Lockhart </td>
   <td style="text-align:right;"> 207 </td>
   <td style="text-align:right;"> 92 </td>
   <td style="text-align:right;"> 0.4444444 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Noah Sedore </td>
   <td style="text-align:right;"> 68 </td>
   <td style="text-align:right;"> 30 </td>
   <td style="text-align:right;"> 0.4411765 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Brendan Hoffmann </td>
   <td style="text-align:right;"> 488 </td>
   <td style="text-align:right;"> 197 </td>
   <td style="text-align:right;"> 0.4036885 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Elias Cohen </td>
   <td style="text-align:right;"> 149 </td>
   <td style="text-align:right;"> 57 </td>
   <td style="text-align:right;"> 0.3825503 </td>
  </tr>
</tbody>
</table>
---

## Step 4: A graph!

---

## Step 4: A graph!

```r
faceoffs_team %>% 
  ggplot(aes(x = reorder(player, faceoff_perc), 
             y = faceoff_perc, fill = team)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  scale_fill_manual(values = c("#F2A900", "#FF6720", "#862633", 
                               "#00205B", "#010101", "#C8C9C7")) +
  labs(title = "Faceoff Percentages",
       subtitle = "Among players with 50+ faceoffs, from Big Data 
       Cup scouting data set") +
  ylab("Faceoff Win Percentage") +
  geom_text(aes(label = scales::percent(faceoff_perc, 
                                        accuracy = 0.1)), 
            family = "Seravek", hjust = -0.15) +
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     limits = c(0, 0.72)) +
  hanic_theme() +
  theme(legend.title = element_blank(),
        legend.position = "bottom",
        panel.grid.major.y = element_blank(),
        axis.title.y = element_blank())
```

---

## Step 4: A graph!

```r
faceoffs_team %>% 
* ggplot(aes(x = reorder(player, faceoff_perc),
*            y = faceoff_perc, fill = team)) +
* geom_bar(stat = "identity") +
* coord_flip() +
  scale_fill_manual(values = c("#F2A900", "#FF6720", "#862633", 
                               "#00205B", "#010101", "#C8C9C7")) +
  labs(title = "Faceoff Percentages",
       subtitle = "Among players with 50+ faceoffs, from Big Data 
       Cup scouting data set") +
  ylab("Faceoff Win Percentage") +
  geom_text(aes(label = scales::percent(faceoff_perc, 
                                        accuracy = 0.1)), 
            family = "Seravek", hjust = -0.15) +
  scale_y_continuous(labels = scales::percent_format(accuracy = 1), 
                     limits = c(0, 0.72)) +
  hanic_theme() +
  theme(legend.title = element_blank(),
        legend.position = "bottom",
        panel.grid.major.y = element_blank(),
        axis.title.y = element_blank())
```

---

## Step 4: A graph!

```r
faceoffs_team %>% 
  ggplot(aes(x = reorder(player, faceoff_perc), 
             y = faceoff_perc, fill = team)) + 
  geom_bar(stat = "identity") + 
  coord_flip() + 
* scale_fill_manual(values = c("#F2A900", "#FF6720", "#862633",
*                              "#00205B", "#010101", "#C8C9C7")) +
* labs(title = "Faceoff Percentages",
*      subtitle = "Among players with 50+ faceoffs, from Big Data
*      Cup scouting data set") +
* ylab("Faceoff Win Percentage") +
* geom_text(aes(label = scales::percent(faceoff_perc,
*                                       accuracy = 0.1)),
*           family = "Seravek", hjust = -0.15) +
* scale_y_continuous(labels = scales::percent_format(accuracy = 1),
*                    limits = c(0, 0.72)) +
* hanic_theme() +
* theme(legend.title = element_blank(),
*       legend.position = "bottom",
*       panel.grid.major.y = element_blank(),
*       axis.title.y = element_blank())
```

---

## Learn More

If you want to stick with the hockey theme:

- [my workshop from CMSAC last year](https://meghan.rbind.io/talk/cmsac/)
- [interactive tutorials in RStudio](https://github.com/meghall06/betweenthepipes)

```r
install.packages("devtools")
devtools::install_github("meghall06/betweenthepipes")

# look in the Tutorial pane in the upper-right of RStudio
# or...run:

betweenthepipes::intro()
betweenthepipes::data_manip()
```

---

## Learn More

If you want to stick with the hockey theme:

- [my workshop from CMSAC last year](https://meghan.rbind.io/talk/cmsac/)
- [interactive tutorials in RStudio](https://github.com/meghall06/betweenthepipes)

.center[<img src="figs/hanic/screenshot.png" width="700px"/>]

---

## Learn More

If you want to stick with the hockey theme:

- [my workshop from CMSAC last year](https://meghan.rbind.io/talk/cmsac/)
- [interactive tutorials in RStudio](https://github.com/meghall06/betweenthepipes)

```r
install.packages("devtools")
devtools::install_github("meghall06/betweenthepipes")

# look in the Tutorial pane in the upper-right of RStudio
# or...run:

betweenthepipes::intro()
betweenthepipes::data_manip()
```

Elsewhere:

- [R for Data Science](https://r4ds.had.co.nz/) &nbsp; ⭐
- [R for Excel Users](https://rstudio-conf-2020.github.io/r-for-excel/)
- [STAT 545](https://stat545.com/)

---

class: inverse, center, middle
layout: false

# Thanks!

<i class="fab  fa-twitter "></i> [@MeghanMHall](https://www.twitter.com/MeghanMHall) <br> [meghan.rbind.io](https://meghan.rbind.io/) <br>
Slides created via the R package [xaringan](https://github.com/yihui/xaringan).