R + ggplot2: how to hide missing dates from x-axis?

Say we have the following simple data-frame of date-value pairs, where some dates are missing in the sequence (i.e. Jan 12 thru Jan 14). When I plot the points, it shows these missing dates on the x-axis, but there are no points corresponding to those dates. I want to prevent these missing dates from showing up in the x-axis, so that the point sequence has no breaks. Any suggestions on how to do this? Thanks!

dts <- c(as.Date( c('2011-01-10', '2011-01-11', '2011-01-15', '2011-01-16')))
df <- data.frame(dt = dts, val = seq_along(dts)) 
ggplot(df, aes(dt,val)) + geom_point(开发者_如何学Go) + 
        scale_x_date(format = '%d%b', major='days')

I made a package that does this. It's called bdscale and it's on CRAN and github. Shameless plug.

To replicate your example:

> library(bdscale)
> library(ggplot2)
> library(scales)
> dts <- as.Date( c('2011-01-10', '2011-01-11', '2011-01-15', '2011-01-16'))
> ggplot(df, aes(x=dt, y=val)) + geom_point() + 
    scale_x_bd(business.dates=dts, labels=date_format('%d%b'))

But what you probably want is to load known valid dates, then plot your data using the valid dates on the x-axis:

> nyse <- bdscale::yahoo('SPY') # get valid dates from SPY prices
> dts <- as.Date('2011-01-10') + 1:10
> df <- data.frame(dt=dts, val=seq_along(dts))
> ggplot(df, aes(x=dt, y=val)) + geom_point() + 
    scale_x_bd(business.dates=nyse, labels=date_format('%d%b'), max.major.breaks=10)

Warning message:
Removed 3 rows containing missing values (geom_point). 

The warning is telling you that it removed three dates:

• 15th = Saturday
• 16th = Sunday
• 17th = MLK Day

Turn the date data into a factor then. At the moment, ggplot is interpreting the data in the sense you have told it the data are in - a continuous date scale. You don't want that scale, you want a categorical scale:

require(ggplot2)
dts <- as.Date( c('2011-01-10', '2011-01-11', '2011-01-15', '2011-01-16'))
df <- data.frame(dt = dts, val = seq_along(dts)) 
ggplot(df, aes(dt,val)) + geom_point() + 
        scale_x_date(format = '%d%b', major='days')

versus

df <- data.frame(dt = factor(format(dts, format = '%d%b')), 
                  val = seq_along(dts)) 
ggplot(df, aes(dt,val)) + geom_point()

which produces:

Is that what you wanted?

First question is : why do you want to do that? There is no point in showing a coordinate-based plot if your axes are not coordinates. If you really want to do this, you can convert to a factor. Be careful for the order though :

dts <- c(as.Date( c('31-10-2011', '01-11-2011', '02-11-2011',
           '05-11-2011'),format="%d-%m-%Y"))
dtsf <- format(dts, format= '%d%b')
df <- data.frame(dt=ordered(dtsf,levels=dtsf),val=seq_along(dts))
ggplot(df, aes(dt,val)) + geom_point()

With factors you have to be careful, as the order is arbitrary in a factor,unless you make it an ordered factor. As factors are ordered alphabetically by default, you can get in trouble with some date formats. So be careful what you do. If you don't take the order into account, you get :

df <- data.frame(dt=factor(dtsf),val=seq_along(dts))
ggplot(df, aes(dt,val)) + geom_point()