![]() Then, we create the legend in the figure using the legend() function and finally display the entire figure using the show() method. We assign the label to each scatter plot used as a tag while generating the legend. We have two separate scatter plots in the figure: one represented by x and another by the o mark. Add a Legend to the 2D Scatter Plot in Matplotlib import numpy as np We can generate a legend of scatter plot using the function. Legend is simply the description of various elements in a figure. Add a Legend to the 3D Scatter Plot in Matplotlib.Add a Legend to the 2D Scatter Plot in Matplotlib.The label keyword to a contouring command (e.g.Matplotlib Matplotlib Scatter Plot Matplotlib LegendĬreated: November-03, 2020 | Updated: July-18, 2021 Legend labels can be assigned to ContourSets by passing Using the labels keyword (e.g., labels=). Legend labels can be assigned for each column of a The following core features are unique to proplot: “handle” list and the second is the “label” list). Passing two positional arguments to legend (where the first argument is the The label keyword (e.g., ax.plot(., label='label')) or on-the-fly by Legend labels can be assigned early by calling plotting comamnds with The following coreĬalling legend without positional arguments willĪutomatically fill the legend with the labeled artist in the Somewhat more flexible than their matplotlib counterparts. format ( suptitle = 'Colorbar formatting demo', xlabel = 'xlabel', ylabel = 'ylabel', titleabove = False ) colorbar ( m, loc = 'ul', length = 6, # length is em widths label = 'inset colorbar', tickminor = True, alpha = 0.5, ) fig. colorbar ( m, loc = 'r', length = 1, # length is relative label = 'interior ticks', tickloc = 'left' ) ax. T, extend = 'both', cmap = 'algae', levels = pplt. arange ( 0, 10 ), label = 'line colorbar', ticks = 2 ) # Colorbars from a mappable ax = fig. plot ( # add all at once data, lw = 2, cycle = 'Reds1', cycle_kw = ) ax. subplot ( 121, title = 'On-the-fly legend' ) ax. figure ( share = 0, refwidth = 2.3, suptitle = 'On-the-fly colorbar and legend demo' ) # Legends data = ( state. Import proplot as pplt labels = list ( 'xyzpq' ) state = np. format ( abc = True, xlabel = 'xlabel', ylabel = 'ylabel', suptitle = 'Colorbar and legend location demo' ) legend ( hs, list ( 'jklmn' ), loc = 'r', ncols = 1, frame = False ) # manually override labels fig. legend ( hs, loc = 't', ncols = 5, frame = False ) # automatically infer labels from handles ax. legend ( loc = 'll', label = 'legend label' ) # automatically infer handles and labels ax. plot ( data, lw = 3, cycle = 'ggplot', labels = list ( 'abcde' )) ax. subplot ( 122, title = 'Axes legends', titlepad = '0em' ) data = ( state. ![]() colorbar ( m, loc = 'll', label = 'colorbar label' ) # inset colorbar demonstration # Legends ax = fig. colorbar ( m, loc = 't' ) # title is automatically adjusted ax. subplot ( 121, title = 'Axes colorbars' ) data = state. figure ( share = False, refwidth = 2.3 ) # Colorbars ax = fig. Import proplot as pplt import numpy as np state = np. The below example shows a variety of arrangements of “outer” and “inset” (or, for “inset” locations, the padding between the subplot edge and the inset frame). Tight layout padding relative to the subplot’s tick and axis labels “outer” colorbar or legend from the parent subplot edge and pad controls the space controls the absolute separation of the InsetĬolorbars have optional background “frames” that can be configured (e.g., loc='upper right' or the shorthand loc='ur'). Proplot adds the axes command ,Īnalogous to and equivalent toĬalling with an ax keyword.Ĭolorbar can draw both “outer” colorbars when you requestĪ side location (e.g., loc='right' or the shorthand loc='r') and “inset”Ĭolorbars when you request an inset location Unlike usingībox_to_anchor, the “outer” legend position is adjusted automatically when the Or colorbars on one side, they are “stacked” on top of each other. (e.g., loc='right' or the shorthand loc='r'). Legends along a subplot edge when you request a side location Location (e.g., loc='upper right' or the shorthand loc='ur') and “outer” ![]() can draw both “inset” legends when you request an inset Posssible using the somewhat opaque bbox_to_anchor keyword (see here)Īnd “inset” colorbars are not possible without manually creating and positioning Matplotlib supports drawing “inset” legends and “outer” colorbars using the locĪnd location keyword arguments.
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