Lahman Datasets — LahmanData • Lahman

This dataset gives a concise description of the data files in the Lahman package. It may be useful for computing on the various files.

Usage

data(LahmanData)

Format

A data frame with 24 observations on the following 5 variables.

file: name of dataset
class: class of dataset
nobs: number of observations
nvar: number of variables
title: dataset title

Details

This dataset is generated using vcdExtra::datasets(package="Lahman") with some post-processing.

Examples

data(LahmanData)

# find ID variables in the datasets
IDvars <- lapply(LahmanData[,"file"], function(x) grep('.*ID$', colnames(get(x)), value=TRUE))
names(IDvars) <- LahmanData[,"file"]
str(IDvars)
#> List of 27
#>  $ AllstarFull        : chr [1:5] "playerID" "yearID" "gameID" "teamID" ...
#>  $ Appearances        : chr [1:4] "yearID" "teamID" "lgID" "playerID"
#>  $ AwardsManagers     : chr [1:4] "playerID" "awardID" "yearID" "lgID"
#>  $ AwardsPlayers      : chr [1:4] "playerID" "awardID" "yearID" "lgID"
#>  $ AwardsShareManagers: chr [1:4] "awardID" "yearID" "lgID" "playerID"
#>  $ AwardsSharePlayers : chr [1:4] "awardID" "yearID" "lgID" "playerID"
#>  $ Batting            : chr [1:4] "playerID" "yearID" "teamID" "lgID"
#>  $ BattingPost        : chr [1:4] "yearID" "playerID" "teamID" "lgID"
#>  $ CollegePlaying     : chr [1:3] "playerID" "schoolID" "yearID"
#>  $ Fielding           : chr [1:4] "playerID" "yearID" "teamID" "lgID"
#>  $ FieldingOF         : chr [1:2] "playerID" "yearID"
#>  $ FieldingOFsplit    : chr [1:4] "playerID" "yearID" "teamID" "lgID"
#>  $ FieldingPost       : chr [1:4] "playerID" "yearID" "teamID" "lgID"
#>  $ HallOfFame         : chr [1:2] "playerID" "yearID"
#>  $ HomeGames          : chr(0) 
#>  $ Managers           : chr [1:4] "playerID" "yearID" "teamID" "lgID"
#>  $ ManagersHalf       : chr [1:4] "playerID" "yearID" "teamID" "lgID"
#>  $ Parks              : chr(0) 
#>  $ People             : chr [1:3] "playerID" "bbrefID" "retroID"
#>  $ Pitching           : chr [1:4] "playerID" "yearID" "teamID" "lgID"
#>  $ PitchingPost       : chr [1:4] "playerID" "yearID" "teamID" "lgID"
#>  $ Salaries           : chr [1:4] "yearID" "teamID" "lgID" "playerID"
#>  $ Schools            : chr "schoolID"
#>  $ SeriesPost         : chr "yearID"
#>  $ Teams              : chr [1:5] "yearID" "lgID" "teamID" "franchID" ...
#>  $ TeamsFranchises    : chr "franchID"
#>  $ TeamsHalf          : chr [1:4] "yearID" "lgID" "teamID" "divID"
# vector of unique ID variables
unique(unlist(IDvars))
#>  [1] "playerID" "yearID"   "gameID"   "teamID"   "lgID"     "awardID" 
#>  [7] "schoolID" "bbrefID"  "retroID"  "franchID" "divID"   

# which datasets have playerID?
names(which(sapply(IDvars, function(x) "playerID" %in% x)))
#>  [1] "AllstarFull"         "Appearances"         "AwardsManagers"     
#>  [4] "AwardsPlayers"       "AwardsShareManagers" "AwardsSharePlayers" 
#>  [7] "Batting"             "BattingPost"         "CollegePlaying"     
#> [10] "Fielding"            "FieldingOF"          "FieldingOFsplit"    
#> [13] "FieldingPost"        "HallOfFame"          "Managers"           
#> [16] "ManagersHalf"        "People"              "Pitching"           
#> [19] "PitchingPost"        "Salaries"           

################################################
# Visualize relations among datasets via an MDS
################################################
# jaccard distance between two sets; assure positivity
jaccard <- function(A, B) {
  max(1 - length(intersect(A,B)) / length(union(A,B)), .00001)
}  

distmat <- function(vars, FUN=jaccard) {
  nv <- length(vars)
  d <- matrix(0, nv, nv, dimnames=list(names(vars), names(vars)))
  
  for(i in 1:nv) {
    for (j in 1:nv) {
      if (i != j) d[i,j] <- FUN(vars[[i]], vars[[j]])
    }
  }
  
  d[is.nan(d)] = 0
  
  d
}

# do an MDS on distances
distID <- distmat(IDvars)
config <- cmdscale(distID)

pos=rep(1:4, length=nrow(config))
plot(config[,1], config[,2], xlab = "", ylab = "", asp = 1, axes=FALSE,
  main="MDS of ID variable distances of Lahman tables")
abline(h=0, v=0, col="gray80")
text(config[,1], config[,2], rownames(config), cex = 0.75, pos=pos, xpd=NA)