The size of the markers in the plot is defined in part by the s argument. Use the plt.scatter() function to plot the data.īy providing a value to the scatter() function's "s" argument, we can modify the marker size. Use the s option to choose the size of the marker you want. AlgorithmĪ general, step-by-step approach for changing marker size in Matplotlib is − Here, the “s” parameter specifies the marker size. The syntax to adjust marker size in Matplotlib is as follows − plt.scatter(x_values, y_values, s=marker_size) We'll show you how to alter the marker size in Matplotlib using examples of Python code in this post. It is possible to alter the marker size to draw attention to crucial details or to develop more aesthetically pleasing plots. With Matplotlib, a wide variety of marker shapes are provided, including circles, squares, triangles, diamonds, and more. Markers are commonly used in conjunction with other charting methods to enhance the readability and comprehension of data. Just a few of the attributes that may be changed. Plt.In a plot, a marker is a symbol that designates a single data point. The key is to map the scatter PathCollection to a HandlerPathCollection with an updating function being set to it. This has the advantage that it would not use any "private" methods and works even with other objects than scatters present in the legend. Plt.legend(,, loc="lower left", markerscale=2, The only real downside is that you have to construct the legend explicitly from lists of objects and labels, but this is a well-documented matplotlib feature so it feels pretty safe to use. This is nice because it doesn't require placing an object in your axes (potentially triggering a resize event), and it doesn't require use of any hidden attributes. You can make a Line2D object that resembles your chosen markers, except with a different marker size of your choosing, and use that to construct the legend. But now you can use everything scatter offers. No need to touch the source, even though this is quite a hack. Now the _sizes (another underscore property) does the trick. Lgnd = plt.legend(loc="lower left", scatterpoints=1, fontsize=10) A better hack: import matplotlib.pyplot as plt It may break down at any update in matplotlib. the marker size changed manually to be 6 points for both markers in the legendĪs you can see, this utilizes hidden underscore properties ( _legmarker) and is bug-ugly.scatter changed into a plot, which changes the marker scaling (hence the sqrt) and makes it impossible to use changing marker size (if that was intended).#change the marker size manually for both lines Lgnd = plt.legend(loc="lower left", numpoints=1, fontsize=10) However, I have a hack which does probably what you want: import matplotlib.pyplot as plt The scatter plots are especially challenging in this respect. Neither of these is very much fun, though #1 seems to be easier. The transform (scaling) has to take the original size into account.
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