Develop Reference

How to set gridlines behind boxplots in seaborn/matplotlib? [duplicate]

In Matplotlib, I make dashed grid lines as follows:
fig = pylab.figure()
ax = fig.add_subplot(1,1,1)
ax.yaxis.grid(color='gray', linestyle='dashed')
however, I can't find out how (or even if it is possible) to make the grid lines be drawn behind other graph elements, such as bars. Changing the order of adding the grid versus adding other elements makes no difference.
Is it possible to make it so that the grid lines appear behind everything else?

According to this - http://matplotlib.1069221.n5.nabble.com/axis-elements-and-zorder-td5346.html - you can use Axis.set_axisbelow(True)
(I am currently installing matplotlib for the first time, so have no idea if that's correct - I just found it by googling "matplotlib z order grid" - "z order" is typically used to describe this kind of thing (z being the axis "out of the page"))

To me, it was unclear how to apply andrew cooke's answer, so this is a complete solution based on that:
ax.set_axisbelow(True)
ax.yaxis.grid(color='gray', linestyle='dashed')

If you want to validate the setting for all figures, you may set
plt.rc('axes', axisbelow=True)
or
plt.rcParams['axes.axisbelow'] = True
It works for Matplotlib>=2.0.

I had the same problem and the following worked:
[line.set_zorder(3) for line in ax.lines]
fig.show() # to update
Increase 3to a higher value if it does not work.

You can also set the zorder kwarg in matplotlib.pyplot.grid
plt.grid(which='major', axis='y', zorder=-1.0)

You can try to use one of Seaborn's styles. For instance:
import seaborn as sns
sns.set_style("whitegrid")
Not only the gridlines will get behind but the looks are nicer.

For some (like me) it might be interesting to draw the grid behind only "some" of the other elements. For granular control of the draw order, you can use matplotlib.artist.Artist.set_zorder on the axes directly:
ax.yaxis.grid(color='gray', linestyle='dashed')
ax.set_zorder(3)
This is mentioned in the notes on matplotlib.axes.Axes.grid.

Incomple text while saving seaborn figures [duplicate]

Updated MRE with subplots
I'm not sure of the usefulness of the original question and MRE. The margin padding seems to be properly adjusted for large x and y labels.
The issue is reproducible with subplots.
Using matplotlib 3.4.2
fig, axes = plt.subplots(ncols=2, nrows=2, figsize=(8, 6))
axes = axes.flatten()
for ax in axes:
ax.set_ylabel(r'$\ln\left(\frac{x_a-x_b}{x_a-x_c}\right)$')
ax.set_xlabel(r'$\ln\left(\frac{x_a-x_d}{x_a-x_e}\right)$')
plt.show()
Original
I am plotting a dataset using matplotlib where I have an xlabel that is quite "tall" (it's a formula rendered in TeX that contains a fraction and is therefore has the height equivalent of a couple of lines of text).
In any case, the bottom of the formula is always cut off when I draw the figures. Changing figure size doesn't seem to help this, and I haven't been able to figure out how to shift the x-axis "up" to make room for the xlabel. Something like that would be a reasonable temporary solution, but what would be nice would be to have a way to make matplotlib recognize automatically that the label is cut off and resize accordingly.
Here's an example of what I mean:
import matplotlib.pyplot as plt
plt.figure()
plt.ylabel(r'$\ln\left(\frac{x_a-x_b}{x_a-x_c}\right)$')
plt.xlabel(r'$\ln\left(\frac{x_a-x_d}{x_a-x_e}\right)$', fontsize=50)
plt.title('Example with matplotlib 3.4.2\nMRE no longer an issue')
plt.show()
The entire ylabel is visible, however, the xlabel is cut off at the bottom.
In the case this is a machine-specific problem, I am running this on OSX 10.6.8 with matplotlib 1.0.0

Use:
import matplotlib.pyplot as plt
plt.gcf().subplots_adjust(bottom=0.15)
# alternate option without .gcf
plt.subplots_adjust(bottom=0.15)
to make room for the label, where plt.gcf() means get the current figure. plt.gca(), which gets the current Axes, can also be used.
Edit:
Since I gave the answer, matplotlib has added the plt.tight_layout() function.
See matplotlib Tutorials: Tight Layout Guide
So I suggest using it:
fig, axes = plt.subplots(ncols=2, nrows=2, figsize=(8, 6))
axes = axes.flatten()
for ax in axes:
ax.set_ylabel(r'$\ln\left(\frac{x_a-x_b}{x_a-x_c}\right)$')
ax.set_xlabel(r'$\ln\left(\frac{x_a-x_d}{x_a-x_e}\right)$')
plt.tight_layout()
plt.show()

In case you want to store it to a file, you solve it using bbox_inches="tight" argument:
plt.savefig('myfile.png', bbox_inches="tight")

An easy option is to configure matplotlib to automatically adjust the plot size. It works perfectly for me and I'm not sure why it's not activated by default.
Method 1
Set this in your matplotlibrc file
figure.autolayout : True
See here for more information on customizing the matplotlibrc file: http://matplotlib.org/users/customizing.html
Method 2
Update the rcParams during runtime like this
from matplotlib import rcParams
rcParams.update({'figure.autolayout': True})
The advantage of using this approach is that your code will produce the same graphs on differently-configured machines.

plt.autoscale() worked for me.

You can also set custom padding as defaults in your $HOME/.matplotlib/matplotlib_rc as follows. In the example below I have modified both the bottom and left out-of-the-box padding:
# The figure subplot parameters. All dimensions are a fraction of the
# figure width or height
figure.subplot.left : 0.1 #left side of the subplots of the figure
#figure.subplot.right : 0.9
figure.subplot.bottom : 0.15
...

There is also a way to do this using the OOP interface, applying tight_layout directly to a figure:
fig, ax = plt.subplots()
fig.set_tight_layout(True)
https://matplotlib.org/stable/api/figure_api.html

for some reason sharex was set to True so I turned it back to False and it worked fine.
df.plot(........,sharex=False)

You need to use sizzors to modify the axis-range:
import sizzors as sizzors_module
sizzors_module.reshape_the_axis(plt).save("literlymylief.tiff")

How can I get matplotlib to show full subplots in an animation?

I'm trying to write a simple immune system simulator. I'm modeling infected tissue as a simple grid of cells and various intracellular signals, and I'd like to animate movement of cells in one plot and the intensity of viral presence in another as the infection progresses. I'm doing so with the matshow function provided by matplotlib. However, when I plot the two next to each other, the full grid gets clipped unless I stretch out the window myself. I can't address the problem at all when saving to an mp4.
Here's the default view, which is identical to what I observe when saving to mp4:
And here's what it looks like after stretching out the viewer window
I'm running Python 2.7.9 with matplotlib 1.4.2 on OS X 10.10.2, using ffmpeg 2.5.2 (installed via Homebrew). Below is the code I'm using to generate the animation. I tried using plt.tight_layout() but it didn't affect the problem. If anyone has any advice as to how to solve this, I'd really appreciate it! I'd especially like to be able to save it without viewing with plt.show(). Thanks!
def animate(self, fname=None, frames=100):
fig, (agent_ax, signal_ax) = plt.subplots(1, 2, sharey=True)
agent_ax.set_ylim(0, self.grid.shape[0])
agent_ax.set_xlim(0, self.grid.shape[1])
signal_ax.set_ylim(0, self.grid.shape[0])
signal_ax.set_xlim(0, self.grid.shape[1])
agent_mat = agent_ax.matshow(self.display_grid(),
vmin=0, vmax=10)
signal_mat = signal_ax.matshow(self.signal_display(virus),
vmin=0, vmax=20)
fig.colorbar(signal_mat)
def anim_update(tick):
self.update()
self.diffuse()
agent_mat.set_data(self.display_grid())
signal_mat.set_data(self.signal_display(virus))
return agent_mat, signal_mat
anim = animation.FuncAnimation(fig, anim_update, frames=frames,
interval=3000, blit=False)
if fname:
anim.save(fname, fps=5, extra_args=['-vcodec', 'libx264'])
else:
plt.show()

According to the matplotlib documentation
Because of how matshow() tries to set the figure aspect ratio to be the one of the array, if you provide the number of an already existing figure, strange things may happen.
I think you're better off using imshow instead (which I believe is what matshow calls. That has an aspect keyword argument which you could use if it doesn't work automatically.
Also according to the matplotlib documentation,
Sets origin to ‘upper’, ‘interpolation’ to ‘nearest’ and ‘aspect’ to equal.
I think you want to do the first two, but leave aspect as auto.

Well, one simple solution would be to just specify the width of the figure when creating it:
fig, (agent_ax, signal_ax) = plt.subplots(1, 2, sharey=True,
figsize=(16,6))

Setting Yaxis in Matplotlib using Pandas

Using Pandas to plot in I-Python Notebook, I have several plots and because Matplotlib decides the Y axis it is setting them differently and we need to compare that data using the same range.
I have tried several variants on: (I assume I'll need to apply the limits to each plot.. but since I can't get one working... From the Matplotlib doc it seems that I need to set ylim, but can't figure the syntax to do so.
df2250.plot(); plt.ylim((100000,500000)) <<<< if I insert the ; I get int not callable and if I leave it out I get invalid syntax. anyhow, neither is right...
df2260.plot()
df5.plot()

I'm guessing this was a feature added after this answer was accepted in 2013; DataFrame.plot() now exposes a ylim parameter that sets the y axis limits:
df.plot(ylim=(0,200))
See pandas documentation for details.

Pandas plot() returns the axes, you can use it to set the ylim on it.
ax1 = df2250.plot()
ax2 = df2260.plot()
ax3 = df5.plot()
ax1.set_ylim(100000,500000)
ax2.set_ylim(100000,500000)
etc...
You can also pass an axes to Pandas plot, so plotting it in the same axes can be done like:
ax1 = df2250.plot()
df2260.plot(ax=ax1)
etc...
If you want a lot of different plots, defining the axes beforehand and within one figure might be the solution that gives you the most control:
fig, axs = plt.subplots(1,3,figsize=(10,4), subplot_kw={'ylim': (100000,500000)})
df2260.plot(ax=axs[0])
df2260.plot(ax=axs[1])
etc...

Using matplotlib, how do I whiten the background of the axis label?

Is there a way to whiten out the background of the axis label so that when it crosses the axis line itself, the latter does not run through it?
For example, this script (the best I managed so far)
#!/usr/bin/python
import matplotlib.pyplot as plt
xx=[1,2,3]
yy=[2,3,4]
dy=[0.1,0.2,0.05]
fig=plt.figure()
ax=fig.add_subplot(111)
ax.errorbar(xx,yy,dy,fmt='ro-',ms=6,elinewidth=4)
ax.set_xlim([0.,3.4])
ax.set_ylim([0.,4.4])
ax.set_xlabel(r'$T/t$',fontsize=16)
ax.set_ylabel(r'$S(\mathbf{Q})L^{1+\eta}$',fontsize=16)
# position the axis labels
ax.xaxis.set_label_coords(1,0)
ax.yaxis.set_label_coords(0.1,0.93)
ax.yaxis.get_label().set_rotation('horizontal')
ax.yaxis.get_label().set_backgroundcolor('w')
#ax.yaxis.get_label().set_zorder(222) #doesn't do the trick
plt.show()
produces almost what I'm looking for, but still the y-axis runs over the label: .

By default, the left spine has a zorder of 2.5. For some reason this seems to cause problems; maybe there's something in the code which only works if they're integral? Anyway, if you add
ax.spines['left'].set_zorder(2)
or more generally
ax.spines['left'].set_zorder(ax.yaxis.get_label().get_zorder()-1)
before the show, it should work. Also, set_ylabel returns the ylab object itself, so if you use "ylab = ax.set_ylabel(stuff)" you can avoid all the ax.yaxis.get_label() calls later.

Does this link help you?
http://matplotlib.sourceforge.net/faq/howto_faq.html#automatically-make-room-for-tick-labels
You can simply shift the y-axis to the right to allows some space for the $S(\mathbf{Q})L^{1+\eta}$ mark be fully placed before the axis line.