data(UStaxWords)
plot(EntireTaxCodeAndRegs/1000 ~ year, UStaxWords, type='b',
ylab='Millions of words in US tax code & regs')
# Write to a file for Wikimedia Commons
svg('UStaxWords.svg')
matplot(UStaxWords$year, UStaxWords[c(2:3, 5:6)]/1000,
type='b', bty='n', ylab='',
ylim=c(0, max(UStaxWords$EntireTaxCodeAndRegs)/1000),
las=1, xlab="", cex.axis=2)
lines(EntireTaxCodeAndRegs/1000~year, UStaxWords, lwd=2)
dev.off()
# lines 1:4 = IncomeTaxCode, otherTaxCode, IncomeTaxRegulations,
# and otherTaxRegulations, respectively
##
## Plotting the original numbers without the adjustment
##
UStax. <- UStaxWords
UStax.[2,c(6:7, 9:10)] <- c(1322, 2960, 1626, 3507)
matplot(UStax.$year, UStax.[c(2:3, 5:6)]/1000,
type='b', bty='n', ylab='',
ylim=c(0, max(UStax.$EntireTaxCodeAndRegs)/1000),
las=1, xlab="", cex.axis=2)
lines(EntireTaxCodeAndRegs/1000~year, UStax., lwd=2)
# Note especially the anomalous behaviour of line 4 =
# otherTaxRegulations. As noted with "details" above,
# otherTaxRegulations could have tripled between 1955 and 1965,
# then fallen by 48 percent between 1965 and 1975. However,
# that does not seem credible, especially since there was no
# corresponding behavior in otherTaxCode.
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