![]() # x,y = event.xdata,event. Is_vis = annot.get_visible() #check if an annotation is visible If event.inaxes != ax: #exit if mouse is not on figure H3 = ax.scatter(x3, 圓, color=colors, s=1)Īrtists = h1 + h2 + #concatenating lists ,, marker='o', color='red')īased off Markus Dutschke" and "ImportanceOfBeingErnest", I (imo) simplified the code and made it more modular.Īlso this doesn't require additional packages to be installed. Names = np.array(list("ABCDEFGHIJKLMNO")) Plt.scatter(points_to_plot, points_to_plot, label=k)īut I really do not enjoy this approach.Here is a code that uses a scatter and shows an annotation upon hovering over the scatter points. Points_to_plot = np.take(data, positions, axis=0) I get into 3 clusters along with label names using matplotlib: Ysklearn - 2 dimensional array contains X and Y coordinates. I could reach an acceptable solution using a for loop in the categories and applying some "filtering" as in: for k, v in ems(): I want each class to have its own color, which I have already coded, but then I want the classes. I want to plot them in either 2D or 3D after I run a clustering algorithm (that color codes the. Basically, I have a list of tuples, each of which functions as a point (so (x, y, z) for example). I believe a similar question to this was asked before, but it didn't really clarify things for me. Each element in the x, y and classes lists corresponds to one point in the plot. Matplotlib: 3D Scatter plots not recognizing labels. I have added this to my code: sc ax 1.scatter (tsne idx, 0, tsne idx, 1, clabelsubset) ax 1.legend (sc.legendelements (), title'clusters') Then your will need to provide a Minimal, Complete, and Verifiable example that includes a toy dataset. For example, I have a list of x and y values, and a list of classes values. It only shows a key with title clusters but has no numbers and color assigned to it. Don't seem to find an option to pass a list of text labels to the plot anywhere, any help appreciated. Using the code above the legend displays the list, not each category. I want to create a Matplotlib scatter plot, with a legend showing the color for each class. For each of the markers in the plot () I want to label them with text from the listofmarkers. Could I get Python to label only as many points as it can without overlapping import matplotlib.pylab as plt, numpy as np npoints 100 xs np.random.rand (npoints) ys np.random.rand (npoints) plt.scatter (xs, ys) labels iter (dir (np)) for x, y, in zip (xs, ys): Ideally I'd condition the next line on whether or not the new label would. Matplotlib treats lists of strings as categorical variables ( Plotting categorical variables ), and by default puts one. ![]() This can easily happen without notice when reading in a comma-delimited text file. The data looks like this: categories = ' for l in labels], label=labels) One common cause for unexpected tick behavior is passing a list of strings instead of numbers or datetime objects. Is it possible to plot the a scatterplot and display a legend without n different entries on legend box? And a list of categories with size 'k < n' and list of category labels to each data point (of course with same dimension as the data, that is, size n).
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