2.3 Data Frames

library(abdwr3edata)

spahn |> 
  dplyr::slice(1:3) |> 
  dplyr::select(1:10)

## # A tibble: 3 × 10
##    Year   Age Tm    Lg        W     L    W.L   ERA     G    GS
##   <dbl> <dbl> <chr> <chr> <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl>
## 1  1942    21 BSN   NL        0     0 NA      5.74     4     2
## 2  1946    25 BSN   NL        8     5  0.615  2.94    24    16
## 3  1947    26 BSN   NL       21    10  0.677  2.33    40    35

spahn[1:3, 1:10]

## # A tibble: 3 × 10
##    Year   Age Tm    Lg        W     L    W.L   ERA     G    GS
##   <dbl> <dbl> <chr> <chr> <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl>
## 1  1942    21 BSN   NL        0     0 NA      5.74     4     2
## 2  1946    25 BSN   NL        8     5  0.615  2.94    24    16
## 3  1947    26 BSN   NL       21    10  0.677  2.33    40    35

2.3.1 Manipulations with Data

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)

## # A tibble: 5 × 6
##    Year   Age     W     L   ERA   FIP
##   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1  1952    31    14    19  2.98 0.345
## 2  1953    32    23     7  2.1  0.362
## 3  1946    25     8     5  2.94 0.415
## 4  1959    38    21    15  2.96 0.675
## 5  1947    26    21    10  2.33 0.695

What do you notice about Spahn’s FIP?

FIP from Fangraphs

Fangraphs library

Fangraphs FIP constants

You can combine data with joins.

batting <- dplyr::bind_rows(NLbatting, ALbatting)

dplyr::dim_desc(NLbatting)

## [1] "[16 x 28]"

dplyr::dim_desc(ALbatting)

## [1] "[14 x 28]"

dplyr::dim_desc(batting)

## [1] "[30 x 28]"

NL <- dplyr::inner_join(NLbatting, NLpitching, by = "Tm")
dplyr::dim_desc(NLpitching)

## [1] "[16 x 34]"

dplyr::dim_desc(NLbatting)

## [1] "[16 x 28]"

dplyr::dim_desc(NL)

## [1] "[16 x 61]"