add chapter 2 materials (#3)

* add chapter 2 materials

* add abdwr3edata package

* run `use_tidy_description()` to tidy imports

---------

Co-authored-by: lgibson7 <“[email protected]”>

Author: trevinflick

02_introduction-to-r.Rmd

@@ -2,9 +2,385 @@
 
 **Learning objectives:**
 
-- THESE ARE NICE TO HAVE BUT NOT ABSOLUTELY NECESSARY
+- Getting started with R
+- Discover different ways to hold data
+- Reading and writing data
+- Tidyverse verbs
+- Understand basic data wrangling
+
+## Downloading and using R
+
+- [Download R language](https://www.r-project.org/)
+- [Rstudio](https://posit.co/products/open-source/rstudio/) (popular IDE)
+- [Positron](https://positron.posit.co/) (new IDE)
+
+- [Setting up macOS as an R data science rig in 2023](https://ivelasq.rbind.io/blog/macos-rig/) by Isabella Velásquez
+
+## Tidyverse
+
+![tidyverse hex logo](images/tidyverse-hex.png)  \
+
+
+
+Packages that make up the Tidyverse
+- **dplyr**, **ggplot2**, **tibble**, **tidyr**, **readr**, **purrr**, **stringr**, **lubridate**, **forcats**
+
+```{r, message=FALSE, eval=TRUE}
+library(tidyverse)
+
+Lahman::Teams |> 
+  dplyr::filter(teamID == "DET") |>
+  dplyr::arrange(desc(yearID)) |>
+  dplyr::select(yearID, name, W, L) |>
+  dplyr::slice_head(n = 10)
+```
+
+Other packages for this book:
+
+```{r, message=FALSE, eval=FALSE}
+remotes::install_github("beanumber/abdwr3edata")
+
+library(abdwr3edata)
+```
+
+## Data Frames
+
+```{r, message=FALSE, eval=TRUE}
+library(abdwr3edata)
+
+spahn |> 
+  dplyr::slice(1:3) |> 
+  dplyr::select(1:10)
+
+spahn[1:3, 1:10]
+```
+
+### Manipulations with Data
+
+![FIP](images/FIP-book.png)  \
+
+```{r, message=FALSE, eval=TRUE}
+spahn <- spahn |> 
+  dplyr::mutate(FIP = (13 * HR + 3 * BB - 2 * SO) / IP)
+
+spahn |> 
+  dplyr::arrange(FIP) |> 
+  dplyr::select(Year, Age, W, L, ERA, FIP) |>
+  dplyr::slice_head(n = 5)
+```
+
+What do you notice about Spahn's FIP?
+
+![FIP from Fangraphs](images/FIP-fg.png)
+
+[Fangraphs library](https://www.fangraphs.com/guts.aspx?type=cn)
+
+[Fangraphs FIP constants](https://www.fangraphs.com/guts.aspx?type=cn)
+
+You can combine data with joins.
+
+```{r, message=FALSE, eval=TRUE}
+batting <- dplyr::bind_rows(NLbatting, ALbatting)
+
+dplyr::dim_desc(NLbatting)
+dplyr::dim_desc(ALbatting)
+dplyr::dim_desc(batting)
+
+NL <- dplyr::inner_join(NLbatting, NLpitching, by = "Tm")
+dplyr::dim_desc(NLpitching)
+dplyr::dim_desc(NLbatting)
+dplyr::dim_desc(NL)
+```
+
+
+## Vectors
+
+A sequence of values of the **same** type (e.g. numeric or character).
+
+If you include multiple types, R will automatically force same type.
+
+```{r, message=FALSE, eval=TRUE}
+# Spahn's wins and losses after the war (this is a code comment)
+
+W <- c(8, 21, 15, 21, 21, 22, 14)
+L <- c(5, 10, 12, 14, 17, 14, 19)
+
+win_pct <- 100 * W / (W + L)
+Year <- seq(from = 1946, to = 1952) # Same: Year <- 1946:1952
+```
+
+R has a lot of built-in functions for vectors
+
+```{r, message=FALSE, eval=TRUE}
+# total wins over post-war span
+sum(W)
+
+# number of seasons post-war
+length(W)
+
+# avg. winning pct.
+mean(win_pct)
+```
+
+Ways to select data with vector index and logicals.
+
+```{r, message=FALSE, eval=TRUE}
+W[c(1, 2, 5)]
+
+W[1 : 4]
+
+W[-c(1, 6)]
+```
+
+How many times did Spahn exceed 20 wins? What years?
+
+```{r, message=FALSE, eval=TRUE}
+W > 20
+
+sum(W > 20)
+
+Year[W > 20]
+```
+
+## Objects and Containers in R
+
+Characters and data frames
+
+```{r, message=FALSE, eval=TRUE}
+Year <- 2008 : 2017
+NL <- c("PHI", "PHI", "SFN", "SLN", "SFN",
+        "SLN", "SFN", "NYN", "CHN", "LAN")
+AL <- c("TBA", "NYA", "TEX", "TEX", "DET",
+        "BOS", "KCA", "KCA", "CLE", "HOU")
+Winner <- c("NL", "AL", "NL", "NL", "NL",
+            "AL", "NL", "AL", "NL", "AL")
+N_Games <- c(5, 6, 5, 7, 4, 7, 7, 5, 7, 7)
+
+WS_results <- tibble::tibble(
+  Year = Year, NL_Team = NL, AL_Team = AL,
+  N_Games = N_Games, Winner = Winner)
+
+WS_results
+
+WS <- WS_results |> 
+  dplyr::group_by(Winner) |> 
+  dplyr::summarize(N = dplyr::n())
+
+WS
+
+ggplot2::ggplot(WS, ggplot2::aes(x = Winner, y = N)) + 
+  ggplot2::geom_col()
+```
+
+Factors
+
+```{r, message=FALSE, eval=TRUE}
+# Alphabetical order
+WS_results |> 
+  dplyr::group_by(NL_Team) |> 
+  dplyr::summarize(N = dplyr::n())
+
+# Use a factor to order by division
+WS_results <- WS_results |>
+  dplyr::mutate(
+    NL_Team = factor(
+      NL_Team, 
+      levels = c("NYN", "PHI", "CHN", "SLN", "LAN", "SFN")
+    )
+  )
+
+# Now ordered by division
+WS_results |> 
+  dplyr::group_by(NL_Team) |> 
+  dplyr::summarize(N = dplyr::n())
+```
+
+Lists
+
+```{r, message=FALSE, eval=TRUE}
+world_series <- list(
+  Winner = Winner, 
+  Number_Games = N_Games,
+  Seasons = "2008 to 2017"
+)
+
+world_series
+```
+Many ways to pull data:
+
+```{r, message=FALSE, eval=TRUE}
+world_series$Number_Games
+
+world_series[[2]]
+
+purrr::pluck(world_series, "Number_Games")
+
+world_series["Number_Games"]
+```
+
+
+```{r, message=FALSE, eval=TRUE}
+WS_results$NL_Team
+
+# same
+dplyr::pull(WS_results, NL_Team)
+```
+
+## Collection of R Commands
+
+```{r, eval=FALSE}
+# We can save this as a script to run later
+
+library(Lahman)
+library(tidyverse)
+
+crcblue <- "#2905a1"
+
+ws <- SeriesPost |>
+  filter(yearID >= 1903, round == "WS", wins + losses < 8)
+ggplot(ws, aes(x = wins + losses)) +
+  geom_bar(fill = crcblue) +
+  labs(x = "Number of games", y = "Frequency")
+```
+
+
+```{r}
+# running the script
+
+source(here::here("scripts/WorldSeriesLength.R"), echo = TRUE)
+```
+
+
+```{r}
+source(here::here("scripts/hr_rates.R"))
+
+# Mickey Mantle stats ffrom 1951 to 1961
+
+HR <- c(13, 23, 21, 27, 37, 52, 34, 42, 31, 40, 54)
+AB <- c(341, 549, 461, 543, 517, 533, 474, 519, 541, 527, 514)
+Age <- 19 : 29
+hr_rates(Age, HR, AB)
+```
+
+
+## Reading and Writing Data
+
+```{r, eval=FALSE}
+# Read data
+getwd()
+
+spahn <- readr::read_csv(here::here("data/spahn.csv"))
+```
+
+
+```{r, eval=FALSE}
+# Write data
+mantle_hr_rates <- hr_rates(Age, HR, AB)
+Mantle <- tibble::tibble(
+  Age, HR, AB, Rates = mantle_hr_rates$y
+)
+
+readr::write_csv(Mantle, here::here("data/mantle.csv"))
+```
+
+
+## Packages
+
+Currently over 20,000 packages available via CRAN
+
+```{r, eval=FALSE}
+# Install package
+install.packages("Lahman")
+
+library(Lahman)
+```
+
+
+Can also download packages via Github
+
+```{r, eval=FALSE}
+remotes::install_github("beanumber/abdwr3edata")
+
+library(abdwr3edata)
+```
+
+Use question mark to learn more about package contents
+
+```{r, eval=FALSE}
+# to learn more about the Batting data set in Lahman
+?Batting
+```
+
+
+## Splitting, Applying, and Combining Data
+
+```{r}
+library(Lahman)
+
+Batting |> 
+  dplyr::filter(yearID >= 1960, yearID <= 1969) |>
+  dplyr::group_by(playerID) |> 
+  dplyr::summarize(HR = sum(HR)) |>
+  dplyr::arrange(desc(HR)) |>
+  dplyr::slice(1:4)
+```
+What if we want to find the top HR hitters for each decade?
+
+```{r}
+hr_leader <- function(data) {
+  data |> 
+    dplyr::group_by(playerID) |> 
+    dplyr::summarize(HR = sum(HR)) |>
+    dplyr::arrange(desc(HR)) |>
+    dplyr::slice(1)
+}
+```
+
+Do you see any potential issues with this function?
+
+```{r}
+Batting_decade <- Batting |>
+  dplyr::mutate(decade = 10 * floor(yearID / 10)) |>
+  dplyr::group_by(decade)
+
+decades <- Batting_decade |>
+  dplyr::group_keys() |>
+  dplyr::pull("decade")
+
+decades
+```
+
+```{r}
+Batting_decade |>
+  dplyr::group_split() |>
+  purrr::map(hr_leader) |>
+  purrr::set_names(decades) |>
+  dplyr::bind_rows(.id = "decade")
+```
+
+## Getting Help
+
+```{r}
+# Will open documentation for the function
+?geom_point
+```
+
+```{r}
+# find all objects that contain this character string
+??geom_point
+```
+
+
+## Further Reading
+
+- [R for Data Science (2e)](https://r4ds.hadley.nz/)
+- [Modern Data Science with R](https://www.routledge.com/Modern-Data-Science-with-R/Baumer-Kaplan-Horton/p/book/9780367191498) $$
+- [A Modern Dive into R and the Tidyverse](https://moderndive.com/)
+- [R for the Rest of Us](https://book.rfortherestofus.com/)
+- [R Packages](https://r-pkgs.org/)
+- [Happy Git and GitHub for the useR](https://happygitwithr.com)
+
+
+
 
-## SLIDE 1 {-}
 
-- ADD SLIDES AS SECTIONS (`##`).
-- TRY TO KEEP THEM RELATIVELY SLIDE-LIKE; THESE ARE NOTES, NOT THE BOOK ITSELF.