Plotly subplot legend how to#
Plotly subplot legend code#

There also exist convenience functions png, Plots.pdf and other unexported helpers. Savefig(p, 'myplot.pdf') # saves the plot from p as a. For example: savefig('myplot.png') # saves the CURRENT_PLOT as a. Saving plots is done by the savefig command. In cases where the plot variable is omitted, Plots.jl uses the global Plots.CURRENT_PLOT automatically. Note that we could have done the same as above using an explicit plot variable, which we call p: x = range(0, 10, length=100)

Plotly subplot legend code#

If we inputted the dots manually, we would need three of them for the sine, exponent, and subtraction, and the resulting code would be less readable. This is a convenience macro that inserts dots for every function call to the right of the macro, ensuring that the entire expression is to be evaluated in an element-wise manner. This is done by the plot! command, where the ! denotes that the command is modifying the current plot. x = range(0, 10, length=100)Īdditionally, we can add more lines by mutating the plot object. Below, forms a 100x2 matrix (100 elements, 2 columns). We can plot multiple lines by plotting a matrix of values where each column is interpreted as a separate line. In Plots.jl, every column is a series, a set of related points which form lines, surfaces, or other plotting primitives. Because of the way Julia works under the hood, this is a difficult problem to solve, but much progress has been made in the past few years to reduce this compilation time. If this is your first plot of the session and it takes a while to show up, this is normal this latency is called the 'time to first plot' problem (or TTFP), and subsequent plots will be fast. The plot is displayed in a plot pane, a stand-alone window or the browser, depending on the environment and backend (see below). To do this in Julia, we insert a dot right after the function call. For the y coordinates, we can create a vector by evaluating sin(x) in an element-wise fashion. For the x coordinates, we can create a range from 0 to 10 of, say, 100 elements. To start, let's plot some trigonometric functions. Depending on your computer, this will take a few seconds: using Plots Basic Plotting: Line PlotsĪfter you have installed Plots.jl via Pkg.add('Plots'), the first step is to initialize the package. It is recommended that the code examples be followed inside the REPL or an interactive notebook.

Plotly subplot legend how to#

Its main goal is to introduce you to the terminology used in the package, how to use Plots.jl in common use cases, and put you in a position to easily understand the rest of the manual. In this example, it would be great to have virginica, versicolor, and setosa listed left to right in the legend (instead of top to bottom).This is a guide for getting you up and running with Plots.jl. Moreover, when placing the legend below the plot, it may look better to have legend items listed horizontally (instead of vertically). Here is an example image of the legend being positioned too low: Because of this, the legend will sometimes accidentally overlap the plot (by being positioned too high up) or be separated from the plot by an awkwardly-large distance (by being positioned too low). However, I notice that this legend position changes based on how I view the plot (the dimensions I make the plot window, etc). I am able to get the legend below and centered to the plot by the following: plot_ly(data = iris, x = Sepal.Length, y = Petal.Length, mode = 'markers', color = Species) %>% layout(legend = list(x = 0.35, y = -0.5)) The default legend items are positioned vertically and located to the right of the plot, as shown here: plot_ly(data = iris, x = Sepal.Length, y = Petal.Length, mode = 'markers', color = Species) One thing I am unable to figure out is how (if it is possible) to reposition legend items so that they are listed horizontally and centered below the plot. I have been tweaking legends in plotly and R.