Ggplot2: remove blank space for weekends and holidays from x-axis dates

Question

works with problems printing stock data in ggplot2 and with the x axis, which contains spaces on weekends and holidays. this one was very useful, but I ran into various problems when trying to use ordered factors.

library(xts) library(grid) library(dplyr) library(scales) library(bdscale) library(ggplot2) library(quantmod) getSymbols("SPY", from = Sys.Date() - 1460, to = Sys.Date(), adjust = TRUE, auto.assign = TRUE) input <- data.frame(SPY["2015/"]) names(input) <- c("Open", "High", "Low", "Close", "Volume", "Adjusted") # i've tried changing rownames() to index(), and the plot looks good, but the x-axis is inaccurate # i've also tried as.factor() xaxis <- as.Date(rownames(input)) input$xaxis <- xaxis p <- ggplot(input) p <- p + geom_segment(aes(x = xaxis, xend = xaxis, y = Low, yend = High), size = 0.50) # body p <- p + geom_segment(aes(x = xaxis - 0.4, xend = xaxis, y = Open, yend = Open), size = 0.90) # open p <- p + geom_segment(aes(x = xaxis, xend = xaxis + 0.4, y = Close, yend = Close), size = 0.90) # close p <- p + scale_y_continuous(scale_y_log10()) p + ggtitle("SPY: 2015") 

The above chart (without red boxes) is generated with the above code segment. And the following diagrams are some of the problems when trying some solutions. First, if I try to use the index of the data frame, I will create a beautiful graph, but the x axis is not accurate; data currently ends in October, but in the chart below it ends in July:

 xaxis <- as.Date(index(input)) 

Secondly, if I try to force the names of the growths to an ordered coefficient, I will lose my horizontal tick data (representing open and closed).

 xaxis <- factor(rownames(input), ordered = TRUE) 

The same question about removing horizontal ticks occurs if I use the bdscale package, but the grid lines are cleaner:

 p <- p + scale_x_bd(business.dates = xaxis) 

Answer 1

You will probably have to treat dates as discrete rather than continuous. This approach with a slightly simplified version of your code might look like this:

 getSymbols("SPY", from = Sys.Date() - 1460, to = Sys.Date(), adjust = TRUE, auto.assign = TRUE) SPY <- SPY["2015/"] colnames(SPY) <- sub("SPY.","", colnames(SPY)) month_brks <- c(1,endpoints(SPY, "months")[-1]) p <- ggplot(data.frame(xaxis=seq(nrow(SPY)), SPY)) p <- p + geom_linerange(aes(x=xaxis, ymin=Low, ymax=High), size=.5) p <- p + geom_text(aes(x = xaxis, y = Open), size = 4., label="-", hjust=.7, vjust=0) # Open p <- p + geom_text(aes(x = xaxis, y = Close), size = 4., label="-", hjust=-.1, vjust=0) # close p <- p + scale_x_continuous(breaks=month_brks, labels=format(index(SPY)[month_brks], "%d %b %Y")) p <- p + labs(title="SPY: 2015", x="Date", y="Price") 

UPDATE

Updated axis label processing.

Answer 2

Well, you can configure it manually, but it's kind of hacks. First, you must use the index so that your observations are numbered from 1 to 188.

  input$xaxis <-index(as.Date(rownames(input))) 

Then your own code:

 p <- ggplot(input) p <- p + geom_segment(aes(x = xaxis, xend = xaxis, y = Low, yend = High), size = 0.50) # body p <- p + geom_segment(aes(x = xaxis - 0.4, xend = xaxis, y = Open, yend = Open), size = 0.90) # open p <- p + geom_segment(aes(x = xaxis, xend = xaxis + 0.4, y = Close, yend = Close), size = 0.90) # close p <- p + scale_y_continuous(scale_y_log10()) + ggtitle("SPY: 2015") 

And finally, I looked at the tab where the breaks should be made, and provided these labels manually:

 p + scale_x_continuous(breaks=input$xaxis[c(1,62,125,188)], labels=c("jan","apr","jul","oct")) 

NOTE HERE that I was lazy and just took the closest date for 1-jan, 1-apr 1-jul and 1-oct, because 1 jan is a holiday, the jan label is below 2-jan. And I put the “oct” label below below 30 seconds, the last entry in input . You can disable the course as you wish.

Of course, you can automate the tag by adding a tag field with a date and retrieve the month.

Answer 3

If you want to use bdscale for this, just tell it to use more grid lines:

 ggplot(input) + geom_segment(aes(x = xaxis, xend = xaxis, y = Low, yend = High), size = 0.50) + # body geom_segment(aes(x = xaxis - 0.4, xend = xaxis, y = Open, yend = Open), size = 0.90) + # open geom_segment(aes(x = xaxis, xend = xaxis + 0.4, y = Close, yend = Close), size = 0.90) + # close ggtitle("SPY: 2015") + xlab('') + ylab('') + scale_x_bd(business.dates=xaxis, max.major.breaks=10, labels=date_format("%b '%y")) # <==== !!!! 

He should put October on the axis there, but that's not so smart. Womp womp. We invite you to participate!

Answer 4

The method below uses a cut to remove spaces between missing dates, and then removes the empty space between the faces to restore the appearance of an unloaded chart.

First, we create a grouping variable, which increases every time a break occurs in the dates (code adapted from this SO answer ). We will use this later for cutting.

 input$group = c(0, cumsum(diff(input$xaxis) > 1)) 

Now we will add the following code to your plot. facet_grid creates a new facet at every place where there is a break in the date sequence due to weekends or holidays. scale_x_date adds basic mark marks once a week and small grid lines for each day, but you can customize this. The theme function eliminates face labels and vertical spaces between faces:

 p + facet_grid(. ~ group, space="free_x", scales="free_x") + scale_x_date(breaks=seq(as.Date("2015-01-01"),max(input$xaxis), "1 week"), minor_breaks="1 day", labels=date_format("%b %d, %Y")) + theme(axis.text.x=element_text(angle=-90, hjust=0.5, vjust=0.5, size=11), panel.margin = unit(-0.05, "lines"), strip.text=element_text(size=0), strip.background=element_rect(fill=NA)) + ggtitle("SPY: 2015") 

Here we get the plot. Spaces for weekends and holidays have disappeared. Major gaps occur every week. I set the weeks in the scale_x_date breaks argument to start on Thursday, since none of the holidays fell on Thursday, and so each face has a large date mark. (In contrast, default breaks will fall on Monday. Since holidays often fall on Monday, weeks with Mondays will not have a large default mark with breaks by default.) Note, however, that the interval between the main breaks essentially varies depending on how many days the market was open this week.

Answer 5

Failed to get OHLC to work - think you need a custom geom .

I know that this is not exactly what you asked for, but can I seduce you with a delicious candlestick chart?

 library(dplyr) library(bdscale) library(ggplot2) library(quantmod) library(magrittr) library(scales) getSymbols("SPY", from = Sys.Date() - 1460, to = Sys.Date(), adjust = TRUE, auto.assign = TRUE) input <- data.frame(SPY["2015/"]) %>% set_names(c("open", "high", "low", "close", "volume", "adjusted")) %>% mutate(date=as.Date(rownames(.))) input %>% ggplot(aes(x=date, ymin=low, ymax=high, lower=pmin(open,close), upper=pmax(open,close), fill=open<close, group=date, middle=pmin(open,close))) + geom_boxplot(stat='identity') + ggtitle("SPY: 2015") + xlab('') + ylab('') + theme(legend.position='none') + scale_x_bd(business.dates=input$date, max.major.breaks=10, labels=date_format("%b '%y"))