Sample financial data is essential for illustrating financial plotting. Fortunately, the gnuplot distribution comes with an appropriate sample datafile. In case you don't have it, we have provided a copy called finance.dat. Make sure it's in your current directory so that gnuplot can find it. You are welcome, of course, to use your own data, but it must be in the correct format. Each line of the file represents a separate data point, and consists of (at least) five numbers, separated by spaces: date open low high close.

An example of a line from such a datafile would look similar to the following:

3/11/2011  76.15  76.63  75.2  75.35

Enter the following commands while you are in the directory containing the datafile:

set bars 2
plot [0:100] 'finance.dat' using 0:2:3:4:5 notitle with financebars

This makes the conventional financial graph showing the high, low, open, and close prices for a stock. If you are reading this recipe, you no doubt already know why you want this type of plot.

The default size of the tics for the opening and closing prices is quite small; the first command makes it longer. The second command sets the range, chooses the file, and specifies the columns to use for the finance plot.

We're going to plot a part of our file parabola.text, so make sure that's still available. Of course, if you have your own sorted statistical data that will probably be more interesting.

Type the following command to make a histogram plot:

plot [-2:2] 'parabola.text' with histeps

As we can see, rather than drawing a line through a series of x-y points, the histeps style draws a staircase composed of horizontal and vertical line segments. The vertical lines are drawn not at the actual x-coordinates given in the data, but at the average values of neighboring x-coordinates. This is the usual way to construct a histogram, where each box represents "how much" is contained in each interval between two x-values.

We are going to reuse our datafile parabolaCircles.text.

The script that produced the stacked histogram is as follows:

set style fill solid 1.0 border lt -1
set style data histograms
set style histogram rowstacked
plot [0:40] 'parabolaCircles.text' using (-$2),\'' using (20*$3) notitle

The first line requests histogram bars filled with a solid color, and with a black border. Without this, the bars are plotted unfilled, which makes the plot more difficult to interpret.

The next two lines specify that data from files should be plotted using histograms; the rowstacked style means that data from each row in the file will be plotted together in one vertical stack.

In the last line, we have chosen to illustrate how to do simple calculations on data columns; the expression is enclosed in parentheses, the column number is preceded with a dollar sign, and the familiar Fortran or C type syntax works just the way you would expect. So we have flipped our parabola back "right side up" with a negative sign, and increased the magnitude of our random numbers by multiplying by 20. (This file was used to plot circles with random diameters in the Plotting circles recipe in this chapter. The random numbers were scaled to give appropriately sized circles, but are too small to give a good illustration of the stacked histogram here. Rather than generating new data, some simple arithmetic allows us to reuse the file.)

We are going to continue to wear out our datafile parabolaCircles.text.

Following are the commands used to produce a multiple histogram plot:

set style fill solid 1.0 border lt -1
set style data histograms
plot [0:40] 'parabolaCircles.text' using (-$2),\'' using (20*$3) notitle

The shrewd reader will have noticed that this is the same recipe as the previous one, with the line set style histogram rowstacked removed. Here, we see the default multiple histogram style.

Keep the datafile parabolaCircles.text ready again.

Following is the script for producing a basic data set plot with errorbars:

set pointsize 3
set bars 3
plot [1:3] 'parabolaCircles.text' using 1:(-$2):3 with errorbars,\'' using 1:(-$2):3  pt 7 notitle

We are using our trusty parabola plus the random number file again; here the random numbers will stand in for errors.

The default point size in gnuplot is quite small; the first line in the recipe increases this. This is especially important for presentations, where increasing the size of various plot elements will make your projected slides far easier to see. The second line increases the size of the small horizontal bars on the ends of the error bars; the default is rather small and hard to see. The third line selects the range, flips the parabola as before, and selects the error bars style. If we omit the portion after the comma, the error bars alone are plotted, with another small horizontal bar indicating the data values. This is OK, but the graph is easier to interpret if we plot a more distinct symbol at each data point; that's what the component after the comma does. We use the special file designator '' to mean the file already mentioned; pt is short for point type, and pt 7 gives a solid circle on most terminals. Finally, notitle prevents a second, redundant entry in the legend.

Error bars can be combined with some of the other plot styles. To create the following figure, which combines a box plot with error bars, change the last line in the recipe to the following commands:

set style fill pattern 2 border lt -1
plot [1:3] 'parabolaCircles.text' using 1:(-$2):3 with boxerrorbars

We've just changed errorbars to boxerrorbars, but first we set the fill pattern to a fine hatching pattern, (this will depend on your output device, try the command test to see them) and asked for a black border to be drawn around the boxes.

This is the same data plotted in the previous figure, in a different style.

We've borrowed the demo file candlesticks.dat that comes with the gnuplot distribution; make sure it's in your current directory. If you want to use your own data instead, each line of the file must be in the following format:

x  whisker_min  box_min  mean  box_high   whisker_high

Feed the following script to gnuplot to get the whisker plot:

set xrange [0:11]
set yrange [0:10]
set boxwidth 0.2
plot 'candlesticks.dat' using 1:3:2:6:5 with candlesticks lt -1 lw 2 whiskerbars,\
    '' using 1:4:4:4:4 with candlesticks lt -1 lw 2 notitle

The first two lines set the x and y ranges of the axes; they are set to give a little room around the data. The next line sets the boxwidth—the width of the rectangle showing the extent of the central part of the distribution (the default is very skinny). Next comes the plot command, split here over two lines. The order of the fields expected by the candlestick style is x box_min whisker_min whisker_high box_high, which is not in the same order as our datafile, so we need to use the using command to put the columns in the right order for plotting. The first plot command also specifies the line type lt to be -1 for solid black and a line width is set to 2; whiskerbars means put the little caps on the end of the whiskers. The second plot command—starting on the last line—plots from the same datafile, but employs a trick to use the 4th column—containing the mean value—repeatedly, effectively collapsing the box ends and whiskers down to the mean, all just to plot the little horizontal line in the middle of the boxes. This may seem like a convoluted method, but it ensures that the lines indicating the mean values are in the right places and have exactly the correct width to lie within the boxes.

Some people prefer their whisker plot boxes to be filled in with a solid color or pattern. To get this, before issuing the plot command try the following command:

set style fill solid

or

set style fill pattern n

The following script illustrates the use of the impulses style:

set samples 30
plot [0:2*pi] sin(x) with impulses lw 2

The first command set the number of points used to sample or plot the function. The plot command tells gnuplot to use the impulse style, which draws a line from the x-axis to each y value; the thickness of the line is given by lw 2.

A "stem plot" is sometimes used in electrical engineering. It is similar to the impulse plot, but with a mark at the end of each stick; this allows the eye to more easily follow the trend of the data; conversely, the sticks make it easier to read the graph, especially when the data is sparse, compared with a simple point plot. Use the following recipe to create a stem plot of a decaying sine wave, illustrated in the following figure:

set samples 50
plot [0:4*pi] exp(-x/4.)*sin(x) with impulses lw 2 notitle,\exp(-x/4.)*sin(x) with points pt 7

As you can see, we have plotted the same function twice. The first time through plot the impulses, as in the previous script, and the second time we plot the function again with points to draw the dots.

The previous plot shows a typical exponentially damped sine wave; it represents, for example, the motion of a pendulum with friction.

The following script creates the previous figure:

set samples 1000
set parametric
plot sin(7*t), cos(11*t) notitle

We want more samples than the default 100 for a smoother plot, hence the first line. The second line (highlighted) changes the way gnuplot interprets plot commands; now the two functions (in the third line) are understood to provide x and y coordinates in the plane as the parameter t is varied. Once we say set parametric, then we can say plot x(t), y(t), and the plot will trace out a curve given by x and y as t is varied between the limits given in trange.

The range of values that t varies through to draw the plot defaults to [-5:5]. Try out different ranges to see what happens by setting the trange. For example, you can say set trange [0:2] and then replot to see the effect.

Following is an example of how to use polar coordinates to get the spiral shown in the previous illustration:

set xtics axis nomirror
set ytics axis nomirror
set zeroaxis
unset border
set samples 500
set polar
plot [0:12*pi] t

The first three lines create a pair of axes that intersect at the origin in the center of the graph. This works for polar plots too, where we are measuring the radius from the center. The unset border line removes the frame that has served up to now as axes for our rectangular coordinate plots. Next, we increase the number of samples for a smooth plot. The crucial, highlighted line set polar changes to polar (r-θ) coordinates from the default rectangular (x-y). In the plot command, t is now a dummy variable that passes through the given angular range (default [0:2*pi], changed to [0:12*pi] here), and the provided function (r) is a function of t, in this case the identity, that yields a circular spiral.