https://github.com/cran/XML
Tip revision: 5ca06dbbc4748f147c312def04189d98af4b8b55 authored by ORPHANED on 19 August 2018, 08:11:10 UTC
version 3.98-1.16
version 3.98-1.16
Tip revision: 5ca06db
itunes.R
# convert i
# xsltproc itunes.xsl ~/Music/iTunes/iTunes\ Music\ Library.xml > itunes.xml
# or with Sxslt
#
# user system elapsed
# 7.514 0.090 7.981
system.time({
library(Sxslt)
doc = xsltApplyStyleSheet("~/itunes.xml", "~/Projects/org/omegahat/XML/RS/examples/itunes.xsl")
top = xmlRoot(doc$doc)
songs.xsl = xmlApply(top, function(x) xmlSApply(x, xmlValue))
})
#####################
# As tempting as it is to take the xmlRoot() in this next command,
# that will allow the XML document to be freed and then a crash will ensue.
doc = xmlInternalTreeParse("~/Projects/org/omegahat/XML/RS/examples/itunes.xml")
# fields = unique(unlist(xmlApply(top, names)))
songs = xmlApply(xmlRoot(doc), function(x) xmlSApply(x, xmlValue))
########################
# Working form the original format of /plist/dict/dict/dict/
doc = xmlInternalTreeParse("~/itunes.xml")
dicts = doc["/plist/dict/dict/dict"]
transform =
function(dict)
{
vals = xmlSApply(dict, xmlValue)
i = seq(1, by = 2, length = length(vals)/2)
structure(vals[i + 1], names = gsub(" ", "_", vals[i]))
}
songs = lapply(dicts, transform)
# For reading, xpath and lapply()
# user system elapsed
# 6.784 0.073 7.153
##########################################
# distribution of bit rates for sampling of the sound.
table(as.numeric(sapply(songs, "[[", "Bit_Rate")))
# How often each song was played.
hist(as.numeric(sapply(songs, "[[", "Play_Count")))
# Number of songs on each album
hist(table(sapply(songs, "[", "Album")))
# Year song was recorded (?)
hist(as.numeric(sapply(songs, "[", "Year")))
# Song size
hist(as.numeric(sapply(songs, "[", "Total_Time")))
# Album time
album.time = tapply(songs, sapply(songs, "[", "Album"), function(x) sum(as.numeric(sapply(x, "[", "Total_Time"))/1000))
dateAdded = as.POSIXct(strptime(sapply(songs, "[", "Date_Added"), "%Y-%m-%dT%H:%M:%S"))
#XXX
hist(as.numeric(dateAdded))
# Artists with most songs
sort(table(sapply(songs, "[", "Artist")), decreasing = TRUE)[1:40]
# How many songs on single and double "albums"
table(sapply(songs, "[", "Disc_Number"))
table(sapply(songs, "[", "Kind"))
table(sapply(songs, "[", "Genre"))
# Check the sampling rate for points off the line.
plot(as.numeric(sapply(songs, "[", "Total_Time")), as.numeric(sapply(songs, "[", "Size")))