![]() ![]() ✅ Updated regularly for free (latest update in April 2021) Let's start off by plotting the generosity score against the GDP per capita: import matplotlib.pyplot as pltĪx.scatter(x = df, y = df) Change Marker Size in Matplotlib Scatter Plot ![]() Then, we can easily manipulate the size of the markers used to represent entries in this dataset. We'll use the World Happiness dataset, and compare the Happiness Score against varying features to see what influences perceived happiness in the world: import pandas as pdĭf = pd.read_csv( 'worldHappiness2019.csv') In this tutorial, we'll take a look at how to change the marker size in a Matplotlib scatter plot. Much of Matplotlib's popularity comes from its customization options - you can tweak just about any element from its hierarchy of objects. The markersize is only the width (not the area) of the marker: ax.Matplotlib is one of the most widely used data visualization libraries in Python. If even gets more confusing if you use plot (which is faster if all markers should have the same size as the docs state as "Notes"). #ax.plot(x_data, y_data, "o",markersize=2*r_)Īs soon as you add an edge (so a non-zero border around the markers), they will overlap: So calculating the area is not pi * r_**2 but rather a square: (2*r_)**2 # open figureĪx.scatter(x_data, y_data, s=marker_size,linewidths=1) one would never calculate the actual area of the symbol). We are not talking about the area of the symbol (in this case a circle) but of a bounding box of the marker (imagine, you want to control the size of a star or an asterix as marker. This is due a misunderstanding of the area of the markers. This is a rather tedious idea, because you need to plot the data twice but you keep the autosizing of the axes. Scl = ax.get_xlim() - ax.get_xlim()Īx.scatter(x_data, y_data, s=marker_size/scl**2, edgecolors='blue',color='red') or scale the markers's size according to the new limits (you will need to know them or do the plotting again) # plot with invisible colorĪx.scatter(x_data, y_data, s=marker_size, color=(0,0,0,0)) R_ = ax.ansform() - ax.ansform() # points # create a n x n square with a marker at each point as dummy data The complete code is: import matplotlib.pyplot as plt So either set the limits to the known size before plotting: ax.set_xlim((0,n-1)) but you are not reducing the marker-size. The bottom line is that you determine the coordinate transformation with the default axis-limits ( (0,1) x (0,1)) and enlarges them afterwards to (-0.75, 15.75)x (-0.75, 15.75). Yes, the problem is that you determine the coordinate-units-to-figure-points size before plotting, so before setting the limits, which influence the coordinate-units but not the overall figure size. The radius is (almost) exactly the r=0.5 coordinate-units that you wanted to have. You can see this if you plot just 4 points ( n=2): ![]() When I run it with s=r_ I get the result on the left and with s=marker_size I get the result on the right of the following image: R_ = ax.ansform() - ax.ansform()Īx.scatter(x_data, y_data, s=marker_size, edgecolors='black') # calculate the marker size so that the markers touch # create a n x n square with a marker at each point Here is an example code of what I want to accomplish, with the results as an image below the code: import matplotlib.pyplot as plt It could also be that running matplotlib from WSL via VcXsrv is causing this problem. I tried transforming the given radius into points via ansData and then calculating the area via pi * r^2, but I did not succeed. I've read in pyplot scatter plot marker size, that the marker size is given as the area of the marker in points^2. I want to have the markers of a scatter plot match a radius given in the data coordinates. ![]()
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