![]() ![]() U, inv = np.unique(c, return_inverse=True)įor cat, color in zip(u, plt.cm.viridis(np.linspace(0,1,len(u)))):Īx.scatter(x, y, color=color, label=cat)Īx.plot(x, y, color=color, ls="", marker="o", label=cat)Ĭmap, norm = from_levels_and_colors(np.arange(0,len(u) 1)-0.5, plt.cm.viridis(np. ![]() Is it possible to provide a list of classes (instead of colors) and then pass a dict like mapping with class -> color?įrom lors import from_levels_and_colorsĬ = np.random.randint(0, n_cats, n).astype(str) What I would like to do is create a scatter plot with custom colors for every class, with a corretly labeled legend and not use loops and the label argument. What would be helpful for me is that the list of lines is returned so i can map the labels by myself.īut maybe I am just using scatter incorretly in this instace. can you tell what exactly you would expect the legend to show in the above example case? Possibly we might think about extending the functionality, but for this it would be good to collect use cases. The reason is that in case you specify the scatter colors as a simple list of colors, no mapping is happening, and therefore we cannot know what to show in the legend (other than maybe the color itself?). In what other manner could I use the c argument then? I found this warning not helpful because I was using the same parameter in both examples Make sure to specify the values to be colormapped via the c argument. \matplotlib\collections.py:960: UserWarning: Collection without array used. That is expected, and there is a warning about it. my example was slightly different before posting. I have made a simple scatterplot using matplotlib showing data from 2 numerical variables (varA and varB) with colors that I defined with a 3rd categorical. I guess you meant to say that the legend_elements of scatter1 is empty, right? Here’s the minimal example: import matplotlib.pyplot as plt plt. Before plt.show (), call plt.legend () your plot will be displayed with a legend. Matplotlib backend ( print(matplotlib.get_backend())): 'module://_inline' How to add a legend in Python’s Matplotlib library Label it with the label keyword argument in your plot method.The first legend does not contain anything, since the legend_elements of scatter1 is empty. legend_elements(), loc = "lower right", title = "Classes2") legend_elements(), loc = "upper left", title = "Classes1") legend_elements ( ** kw ), loc = "lower right", title = "Price" ) plt. cmap ( 0.7 ), fmt = "$ ", func = lambda s : np. kw = dict ( prop = "sizes", num = 5, color = scatter. Note how we target at 5 elements here, but obtain only 4 in the # created legend due to the automatic round prices that are chosen for us. The *fmt* ensures to show the price # in dollars. Because we want to show the prices # in dollars, we use the *func* argument to supply the inverse of the function # used to calculate the sizes from above. add_artist ( legend1 ) # Produce a legend for the price (sizes). Markers are automatically accurate In addition, Matplotlib also reflects the different markers in the chart. But that's not the case here since the legend overlaps with one of the dots. Usually, it also places the legend in a good place. legend_elements ( num = 5 ), loc = "upper left", title = "Ranking" ) ax. By default, Matplotlib automatically generates a legend that correctly reflects the colors and labels we passed. setcolor () function which calls the setfacecolor () and setedgecolor () functions. update () function, which in turn calls the. Even though there are 40 different # rankings, we only want to show 5 of them in the legend. Digging through the code, ‘color’ gets used right after the creation of the collection object by calling the. I have successfully created all the charts in a single plot, however I want the legend of scatter chart to be different from that of the line plots. If we draw multiple lines on one graph, we label them individually using. 1 I have to create a visualization where there are multiple line plots (trend lines/moving averages etc.), and multiple scatter charts. scatter ( volume, amount, c = ranking, s = 0.3 * ( price * 3 ) ** 2, vmin =- 3, vmax = 3, cmap = "Spectral" ) # Produce a legend for the ranking (colors). To add a legend we use the plt.legend() function. To plot a scatter in 3D, use the plot method, as the legend does not support Patch3DCollection as is returned by the scatter method of an Axes3D instance. subplots () # Because the price is much too small when being provided as size for ``s``, # we normalize it to some useful point sizes, s=0.3*(price*3)**2 scatter = ax. uniform ( 1, 10, size = 40 ) fig, ax = plt. ![]()
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