![]() Plt.legend(loc='upper center', bbox_to_anchor=(1. ![]() I used Customizing Plot Legends: Legend for Size of Points.I think this would be better as two separate plots.There's no legend for p1 because the size is static.Plt.legend(loc='upper center', bbox_to_anchor=(1.23, 1), ncol=1, fancybox=True, shadow=True, title='s2') P1 = ax1.scatter(df.x, df.y1, s=20, c=df.arr, cmap='Blues_r', norm=norm, marker='x') The use of the following functions, methods, classes and modules is shown in this example: / Download Python source code: scatter. Scatter plots are widely used to represent relation among variables and how change in one affects the other. The scatter () method in the matplotlib library is used to draw a scatter plot. This problem is illustrated by a scatterplot, using matplotlib (you can see the code below). Scatter plots are used to observe relationship between variables and uses dots to represent the relationship between them. When your dataset is big, points of your scatterplot tend to overlap, and your graphic becomes unreadable. ![]() I would like the legend to look like in the figure below (source here), but with the colour bar and size bar put into a single legend, if possible. Overplotting is one of the most common problems in data visualization. My question: How do I create a legend that displays the corresponding y-values for, let's say 5 different dot sizes and 5 different colour nuances? So, the dot size (in ax3) and the dot colour (in ax1 and ax3) are taken from arrays containing floats with all kinds of values in the range. I create two scatterplots with matplotlib in python with this code, the data for the code is here: import matplotlib.pyplot as plt
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