How do I get faceted barplot values to show as negative - r

Question

I'm struggling a bit to make a vertically- faceted barplot. I added a 'thus far' version of my work below. My main issue is that the negative values aren't showing as I'd expect. Shouldn't there be some line, or tick, indicating 0, with negative bars registering below it? The code below should be fully reproducible. You can see several negative values in the final data set I'm trying to plot. I'm getting a rather verbose error beginning with 'Mapping a variable to y and also using stat="bin".' I sense it's likely related to my issue, but I'm not able to find or derive a concrete solution.
Also, as secondary points, if anyone has any advice past the current snag, my goal end- result would be to color those negative bars red, and the positive ones green, to add the 'spdrNames' to the y axis, to label the bars with the actual value, and to remove the illegible values from the x axis.
require('ggplot')
require('reshape')
require('tseries')
spdrTickers = c('XLY','XLP','XLE','XLF','XLV','XLI','XLB','XLK','XLU')
spdrNames = c('Consumer Discretionary','Consumer Staples', 'Energy',
'Financials','Health Care','Industrials','Materials','Technology',
'Utilities')
latestDate =Sys.Date()
dailyPrices = lapply(spdrTickers, function(ticker) get.hist.quote(instrument= ticker, start = "2012-01-01",
end = latestDate, quote="Close", provider = "yahoo", origin="1970-01-01", compression = "d", retclass="zoo"))
perf5Day = lapply(dailyPrices, function(x){(x-lag(x,k=-5))/lag(x,k=-5)})
perf20Day = lapply(dailyPrices, function(x){(x-lag(x,k=-20))/lag(x,k=-20)})
perf60Day = lapply(dailyPrices, function(x){(x-lag(x,k=-60))/lag(x,k=-60)})
names(perf5Day) = spdrTickers
names(perf20Day) = spdrTickers
names(perf60Day) = spdrTickers
perfsMerged = lapply(spdrTickers, function(spdr){merge(perf5Day[[spdr]],perf20Day[[spdr]],perf60Day[[spdr]])})
perfNames = c('1Week','1Month','3Month')
perfsMerged = lapply(perfsMerged, function(x){
names(x)=perfNames
return(x)
})
latestDataPoints = t(sapply(perfsMerged, function(x){return(x[nrow(x)])}))
latestDataPoints = data.frame(cbind(spdrTickers,latestDataPoints))
names(latestDataPoints) = c('Ticker', '1Week','1Month','3Month')
drm = melt(latestDataPoints, id.vars=c('Ticker'))
names(drm) = c('Ticker','Period','Value')
p = ggplot(drm, aes(x=Ticker,y=Value)) + geom_bar() + coord_flip() + facet_grid(. ~ Period)
Yields this:

Answer 1

Somehow you have converted your Value-values to a factor:
str(drm)
'data.frame': 27 obs. of 3 variables:
$ Ticker: Factor w/ 9 levels "XLB","XLE","XLF",..: 9 6 2 3 8 4 1 5 7 9 ...
$ Period: Factor w/ 3 levels "1Week","1Month",..: 1 1 1 1 1 1 1 1 1 2 ...
$ Value : Factor w/ 27 levels "0.0164396430248944",..: 2 4 5 1 8 3 7 6 9 11 ...
Probably happens here:
latestDataPoints = data.frame(cbind(spdrTickers,latestDataPoints))
> str( latestDataPoints )
'data.frame': 9 obs. of 4 variables:
$ Ticker: Factor w/ 9 levels "XLB","XLE","XLF",..: 9 6 2 3 8 4 1 5 7
$ 1Week : Factor w/ 9 levels "0.0164396430248944",..: 2 4 5 1 8 3 7 6 9
$ 1Month: Factor w/ 9 levels "-0.00139291932675571",..: 2 3 1 5 8 4 6 7 9
$ 3Month: Factor w/ 9 levels "-0.0110357512357742",..: 3 2 1 5 9 6 7 8 4
Since just before that step you had a numeric matrix from: t(sapply(perfsMerged, function(x){return(x[nrow(x)])}))
Then doing this:
latestDataPoints[2:4] <- lapply( latestDataPoints[2:4], function(x)
as.numeric(as.character(x)) )
drm = melt(latestDataPoints, id.vars=c('Ticker'))
names(drm) = c('Ticker','Period','Value')
p = ggplot(drm, aes(x=Ticker,y=Value)) + geom_bar() + coord_flip() +
facet_grid(. ~ Period)
png();print(p);dev.off()
Produces:
The construction data.frame(cbind(...)) is a real trap. I've seen is used by supposedly authoritative sources and it is a recurrent source of puzzlement. I think R would be a safer language to use if the interpreter would simply highlight that combination in red (along with as.numeric applied to factors.) When you cbind a character vector to a numeric matrix, you get an all character matrix.