Sometimes it is recommended to run R “as administrator”.
BaskeballAnalizeR, some or all the dependent packages are not automatically installed. Close all R sessions and open a new R session, then type:
reqpacks<- c('ggplot2', 'hexbin', 'plyr', 'dplyr', 'tidyr', 'rlang', 'magrittr', 'ggrepel',
'gridExtra', 'scales', 'MASS', 'directlabels', 'corrplot', 'ggplotify', 'network',
'sna', 'dendextend', 'circlize', 'PBSmapping', 'sp', 'operators', 'stringr', 'GGally',
'statnet', 'common', 'ggnetwork', 'readr')
install.packages(reqpacks)
There was a mistake in the function fourfactors. The corrected version is now online, so you are probably obtaining the right graphs, where the numbers involved are in the order of magnitude of 2 (see the ERRATA CORRIGE of the book “Basketball Data Science”).
Under certain circumstances, some plotting commands of BaskeballAnalizeR can throw the following error:
Error in grid.Call(C_convert, x, as.integer(whatfrom), as.integer(whatto), :
Viewport has zero dimension(s)
This error is not easily reproducible with BaskeballAnalizeR.
In RStudio, it can be generated by setting a small width of the plot area and running the following example:
library(BasketballAnalyzeR)
tm <- c("BOS","CLE","GSW","HOU")
selTeams <- which(Tadd$team %in% tm)
FF.sel <- fourfactors(Tbox[selTeams,], Obox[selTeams,])
plot(FF.sel)
The problem seems connected to the use of the R package ggrepel and a too large legend. See this link for details.
A possible solution is to reduce the length of the legend labels or to split labels over multiple lines using the newline character \n. See this example related to the analysis presented in Section 2.2.1:
tm <- c("BOS","CLE","GSW","HOU")
selTeams <- which(Tadd$team %in% tm)
FF.sel <- fourfactors(Tbox[selTeams,], Obox[selTeams,])
FF.sel$Team <- c("Boston Celtics", "Cleveland Cavaliers","Golden State\nWarriors", "Houston Rockets")
plot(FF.sel)
Otherwise, try to adjust the width of the plot area.
Thanks to Christopher Riccio who reported this problem.
set.seed(7) and/or set.seed(1)), I obtain a different outcome with respect to that reported on the book.It used to be the case that set.seed() would give the same results across R versions, but that’s no longer generally true due to to a little-announced update in R 3.6.0. So, if the version of your R machine is >= 3.6.0, you need to type RNGkind(sample.kind = "Rounding") at the beginning of your working session. This will allow you to obtain the same outcome reported on the book. A warning message about this issue is given when the library BaskeballAnalizeR is uploaded.
set.seed(29)), I obtain a different outcome with respect to that reported on the book.It used to be the case that set.seed() would give the same results across R versions, but that’s no longer generally true due to to a little-announced update in R 3.6.0. So, if the version of your R machine is >= 3.6.0, you need to type RNGkind(sample.kind = "Rounding") at the beginning of your working session. This will allow you to obtain the same outcome reported on the book. A warning message about this issue is given when the library BaskeballAnalizeR is uploaded.
set.seed(1)), I obtain a different outcome with respect to that reported on the book.It used to be the case that set.seed() would give the same results across R versions, but that’s no longer generally true due to to a little-announced update in R 3.6.0. So, if the version of your R machine is >= 3.6.0, you need to type RNGkind(sample.kind = "Rounding") at the beginning of your working session. This will allow you to obtain the same outcome reported on the book. A warning message about this issue is given when the library BaskeballAnalizeR is uploaded.
