![]() I have added this, and wrote a complete script: # Modules #Īxes = seaborn. He produced the necessary syntax I was needing, but as he pointed out, was missing a way to calculate how many lines of legend are required for splitting the legend. But then both calls to ax.legend would have required some extra arguments so that each legend contained only the items we wanted.I took Diziet's answer and expanded on it. We could have, alternatively, given labels to the markers when they were plotted too. The legend for the markers ( leg2) therefore required the lines and labels as arguments when it was instantiated. For example, add the following to the bottom of the above code: leg1.get_lines().set_lw(8)įinally, it's worth mentioning that in the example only the lines were given labels when plotted, meaning that ax.legend() adds only those lines to the leg1. You can use the convenience method getlegendhandleslabels () to get the handles and the text of the labels: axsns. The really great thing is that you can can still manipulate both legends. The first one you instantiate ( leg1) is removed from the figure when you add the second one, but the leg1 object still exists and can be added back with ax.add_artist. ![]() The key is to make sure you have references to the legend objects. # Add second legend for the maxes and mins. If False, no legend data is added and no legend is drawn. If auto, choose between brief or full representation based on number of levels. # Add first legend: only labeled data is included If full, every group will get an entry in the legend. I'm using Python 2.7, seaborn version 0.5.1, and matplotlib version 1.4.3. Each row has a label, differentiating each series. This function provides access to several different axes-level functions that show the. How to Add a Title to Seaborn Plots How to Change the Position of a. Figure-level interface for drawing relational plots onto a FacetGrid. ![]() FacetGrid (datatips, col' day ', hue' sex ', colwrap 2) add density plots to each plot g. Each series has different (x,y) values, and they are stored as floats in my data frame. The following code shows how to create multiple Seaborn plots and add a legend: define grid g sns. # Plot maxima and minima, and keep references to the lines I'm trying to use seaborn's pointplot() to create a multiple-series scatter plot with connected points. One legend is for the lines, and the other is for the markers. So this function creates a new legend, copying over the data from the original object, which is then removed. When plotting multiple plots in the same script, the first plot is correct, but for the rest, the legends are appended which skew the plots. Matplotlib legends do not expose public control over their position parameters. Then you can perform the standard matplotlib changes to features like the x-axis, or use any of the normal controls available through the matplotlib API. In the example here, we plot two lines, then plot markers on their respective maxima and minima. Recreate a plot’s legend at a new location. For the most flexible control with these kind of plots, create your own axes object then add the seaborn plots to it. ![]() ![]() This has been done so that it is possible to call legend() repeatedly to update the legend to the latest handles on the Axesįear not, though: It is still quite simple to add a second legend (or third, or fourth.) to an axes. If you call plt.legend() or ax.legend() more than once, the first legend is removed and a new one is drawn. ![]()
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