venti venti - 19 days ago 7
Python Question

Python, Seaborn: Logarithmic Swarmplot has unexpected gaps in the swarm

Let's look at a swarmplot, made with Python 3.5 and Seaborn on some data (which is stored in a pandas dataframe df with column lables stored in another class. This does not matter for now, just look at the plot):

ax = sns.swarmplot(x=self.dte.label_temperature, y=self.dte.label_current, hue=self.dte.label_voltage, data = df)


Linear y axis

Now the data is more readable if plotted in log scale on the y-axis because it goes over some decades.
So let's change the scaling to logarithmic:

ax.set_yscale("log")
ax.set_ylim(bottom = 5*10**-10)


Log y axis

Well I have a problem with the gaps in the swarms. I guess they are there because they have been there when the plot is created with a linear axis in mind and the dots should not overlap there. But now they look kind of strange and there is enough space to from 4 equal looking swarms.
My question is: How can I force Seaborn to recalculate the position of the dots to create better looking swarms?

Answer

mwaskom hinted to me in the comments how to solve this. It is even stated in the swamplot doku:

Note that arranging the points properly requires an accurate transformation between data and point coordinates. This means that non-default axis limits should be set before drawing the swarm plot.

Setting an existing axis to log-scale and use this for the plot:

    fig = plt.figure() # create figure
    rect = 0,0,1,1 # create an rectangle for the new axis
    log_ax = fig.add_axes(rect) # create a new axis (or use an existing one)
    log_ax.set_yscale("log") # log first
    sns.swarmplot(x=self.dte.label_temperature, y=self.dte.label_current, hue=self.dte.label_voltage, data = df, ax = log_ax)

This yields in the correct and desired plotting behaviour: enter image description here

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