Comments (2)
As things are, that's probably the easiest thing, though not ideal.
Something you could try is along the lines of:
for a in axes[:-1]:
a.set_xscale('log')
that avoids the error and should scale the data. But then you still need to manually fix the ticks in the last axis, which is the one that actually shows the ticks and labels.
from joypy.
FWIW I figured out a way on how to do this, but there might be a better way. I transformed the input data using np.log10()
and then changed the x labels as:
xticks = [int(i.get_text()) for i in ax[-1].get_xticklabels()]
ax[-1].set_xticklabels([10**i for i in xticks])
from joypy.
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from joypy.