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For some reason when I use a zorder with my scatter plot the edges of the points overlap the axis. I tried some of the solutions from [here] (matplotlib axis tick labels covered by scatterplot (using spines)) but they didn't work for me. Is there a way from preventing this from happening?

I understand I could also add an ax.axvline() at my boundaries but that would be an annoying workaround for lots of plots.

xval = np.array([0,0,0,3,3,3,0,2,3,0]) yval = np.array([0,2,3,5,1,0,1,0,4,5]) zval = yval**2-4 fig = plt.figure(figsize=(6,6)) ax = plt.subplot(111) ax.scatter(xval,yval,cmap=plt.cm.rainbow,c=zval,s=550,zorder=20) ax.set_ylim(0,5) ax.set_xlim(0,3) #These don't work ax.tick_params(labelcolor='k', zorder=100) ax.tick_params(direction='out', length=4, color='k', zorder=100) #This will work but I don't want to have to do this for the plot edges every time ax.axvline(0,c='k',zorder=100) plt.show()

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3 Answers 3

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For me the solution you linked to works; that is, setting the z-order of the scatter plot to a negative number. E.g.

xval = np.array([0,0,0,3,3,3,0,2,3,0]) yval = np.array([0,2,3,5,1,0,1,0,4,5]) zval = yval**2-4 fig = plt.figure(figsize=(6,6)) ax = plt.subplot(111) ax.scatter(xval,yval,cmap=plt.cm.rainbow,c=zval,s=550,zorder=-1) ax.set_ylim(0,5) ax.set_xlim(0,3) plt.show()

Test plot with axes sitting on top of scatter points]1

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Thanks for the suggestion. This is an example of another case which has lots of plot components so I need to have a positive zorder on the scatter plot. Otherwise I would have to specify greater negative numbers for everything else.
Ah OK. Have you tried setting the axes zorder e.g. ax.set_zorder(99). This seems to work for me, but only whilst the zorder of the scatter plot is < 4. For some reason I don't understand, when the zorder of the scatter >= 4, the scatter points lie on top of the axes, seemingly irrespective of the axes own zorder.
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You can fix the overlap using the following code with a large number for the zorder. This will work on both the x- and y-axis.

for k,spine in ax.spines.items(): spine.set_zorder(1000)
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This works for me

import numpy as np import matplotlib.pyplot as plt xval = np.array([0,0,0,3,3,3,0,2,3,0]) yval = np.array([0,2,3,5,1,0,1,0,4,5]) zval = yval**2-4 fig = plt.figure(figsize=(6,6)) ax = plt.subplot(111) ax.scatter(xval,yval,cmap=plt.cm.rainbow,c=zval,s=550,zorder=20) ax.set_ylim(-1,6) ax.set_xlim(-1,4) #These don't work ax.tick_params(labelcolor='k', zorder=100) ax.tick_params(direction='out', length=4, color='k', zorder=100) #This will work but I don't want to have to do this for the plot edges every time ax.axvline(0,c='k',zorder=100) plt.show()

Your circle sizes are big enough that they go beyond the axis scope. So we simply change the ylim and xlim

Changed 

ax.set_ylim(0,5) ax.set_xlim(0,3)

to

ax.set_ylim(-1,6) ax.set_xlim(-1,4)

Also, zorder doesn't play a role in pushing the points to edges.

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Thanks for the suggestion but this is an idealized case for what I am doing and I want to keep the limits. My data has values near zero which represents the surface and below that there isn't anything. I don't care too much about but that data but I still need to show its there.

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