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python pyplot legend adjust (location, size)

I am trying to change location of plot legend. Below what I've got for now.
var_list=powiaty_cols[powiaty_cols.str.contains("apart_bel_40")]
for var in var_list:
fig = plt.figure(figsize=(25, 25))
ax = plt.gca()
powiaty.plot(column=var,cmap='Reds', categorical=True,
legend=True, ax=ax,edgecolor='black')
ax.legend(loc='best')
This code is plotting figure but without legend. I've received errors as follows:
No handles with labels found to put in legend.
No handles with labels found to put in legend.
No handles with labels found to put in legend.
No handles with labels found to put in legend.
But without part 'ax.legend(loc='best')' I can get my plot but legend is in upper left corner. Plotted column is filled with integer from 1 to 5. Similar issue is when I'm trying to change size of legend.
Could maybe somebody help in this?

I don't know what powiaty is, but my guess is that you need to get the Axes object back so you can continue modifying it. Try:
ax = powiaty.plot(column=var, cmap='Reds', categorical=True,
legend=True, ax=ax, edgecolor='black'
)

For me worked:
leg = ax.get_legend()
leg.set_bbox_to_anchor((0., 0.1, 0.2, 0.2))

How to do both things together: adjust subplot spacings and place the legend outside of the plot?

I have 9 matplotlib subplots arranged in a grid. I'm trying to do two simple things: (1) adjust subplot spacing to reduce white space, (2) place the legend outside of the plot. Individually, both things are super easy. Together, they don't work: If I place legend outside of the subplots using bbox_to_achnor=(...), subplot spacing gets messed up and subplots_adjust(...) don't work anymore.
UPD: This works for tight spacing:
fig, axes = plt.subplots(3, 3)
plt.subplot(331)
# plot something on every subplot
plt.subplot(339)
# plot something here too
plt.subplots_adjust(wspace=0, hspace=0)
plt.tight_layout()
plt.savefig("blabla.pdf", format="pdf")
And with this code all figures become squeezed:
fig, axes = plt.subplots(3, 3)
plt.subplot(331)
# plot something on every subplot
plt.subplot(339)
# plot something here too
# add outside legend to the first plot
plt.subplot(331)
lgd = plt.legend(ncol=1, loc=2, prop={'size': 10}, bbox_to_anchor=4.2, 0.2))
plt.subplots_adjust(wspace=0, hspace=0)
plt.tight_layout()
plt.savefig("blabla.pdf", format="pdf", bbox_inches="tight", bbox_extra_artists=(lgd,))
Any ideas?

Things will supposedly work fine if you use the legend with the figure object fig. Currently you use it with the last plt object which correspond to the last subfigure 339. Using fig, you don't need a large offset of 4.2 for the bbox_to_anchor. Something like 1.1 or 1.2 should work fine
lgd = fig.legend(ncol=1, loc=2, prop={'size': 10}, bbox_to_anchor=(1.2, 0.2))

Matplotlib "savefig" as pdf, text overlay

If i run this code in python:
titles = ctf01[0,1:]
fig = plt.figure(figsize=(11.69,8.27), dpi=100)
for num in range(len(titles)):
ax = fig.add_subplot(3,4,num+1)
ax.plot(ctf03[1:,num+1], ctf0102[:,num], 'ro')
ax.set_title(titles[num])
plt.tight_layout()
fig.text(0.5, 0.04, 'CTF12', ha='center')
fig.text(0.04, 0.5, 'CTF3', va='center', rotation='vertical')
fig.savefig("example.pdf")
i get this in the pdf file:
I would like to fix the problem with the "figure title" shown in the red circles.
If i set the 0.04 value as an negative value the title runs out of paper.
I also would like to save some space with moving the title of the subplots (green circles) into the diagram. Any idea how i can realize this?
Thanks for help.

try to add before fig.savefig("example.pdf") following line.
plt.tight_layout()
you have it in your script but it should come after text

It looks like you're trying to set the x and y labels for the whole figure, which isn't possible as these can only be set on an Axes object. Fortunately we can work around it by creating an 'invisible' subplot that fills the whole area and set the labels on this.
After plotting your subplots you would create the invisible one with:
label_ax = fig.add_subplot(111, frameon=False)
The frameon argument prevents it from drawing the box that is added by the default style. Then you tell it not to draw tick marks and make the tick labels invisible (we can't just remove them as it will mess up the spacing).
label_ax.tick_params(bottom=False, left=False, labelcolor="none")
Finally, set your labels:
label_ax.set_xlabel("CTF12")
label_ax.set_ylabel("CTF3")
You can adjust the vertical positioning of the plot titles by providing a pad argument to the set_title function. Giving a negative value will push the title into the plot, you'll need trial and error to find the value that works.
Putting it all together (with made-up data):
fig = plt.figure(figsize=(11.69, 8.27), dpi=100)
for i in range(10):
ax = fig.add_subplot(3, 4, i + 1)
ax.plot([1, 2, 3, 4, 5], "ro")
ax.set_title("Plot {}".format(i), pad=-15)
label_ax = fig.add_subplot(111, frameon=False)
label_ax.tick_params(bottom=False, left=False, labelcolor="none")
label_ax.grid(False) # In case the current style displays a grid.
label_ax.set_xlabel("CTF12")
label_ax.set_ylabel("CTF3")
fig.tight_layout()
fig.savefig("example.pdf")
Which gives:

Matplotlib cuts off legend placed outside axes, ignoring bbox_extra_artists parameter in savefig

This question is similar to this one asked 6 years ago. However, their solution is not quite solving my problem; unlike their question, I am dealing with multiple legends, some of which are getting cut off.
I'm trying to create a figure containing multiple legends that sit outside the axes of my graph. I'm following the matplotlib documentation's instructions for creating multiple legends, using add_artist to add all but the final legend to my axes. I then use the bbox_extra_artists parameter in my savefig call as described in the above question to include all my legend objects. As seen in this example output image, the wider legend still gets cut off on the right side.
The code used to generate this plot:
import matplotlib.pyplot as plt
fig = plt.figure()
ax = plt.gca()
for x in [0, 1, 2]:
ax.bar(x+0.5, x+1, width=1, color=['red', 'blue', 'green'][x])
handle1 = plt.Line2D((0,1), (0,0), color='purple')
lgd1 = ax.legend([handle1], ['label1 is very long'], bbox_to_anchor=(1, 1))
ax.add_artist(lgd1)
handle2 = plt.Line2D((0,1), (0,0), color='orange')
lgd2 = ax.legend([handle2], ['label2'], bbox_to_anchor=(1, 0.9))
plt.savefig('output.png', bbox_extra_artists=(lgd1,lgd2), bbox_inches='tight')
Notably, if I change the order in which the legends are added (adding the wider legend first), the problem goes away and both legends are visible as seen here:
handle2 = plt.Line2D((0,1), (0,0), color='orange')
lgd2 = ax.legend([handle2], ['label2'], bbox_to_anchor=(1, 0.9))
ax.add_artist(lgd2)
handle1 = plt.Line2D((0,1), (0,0), color='purple')
lgd1 = ax.legend([handle1], ['label1 is very long'], bbox_to_anchor=(1, 1))
plt.savefig('output.png', bbox_extra_artists=(lgd1,lgd2), bbox_inches='tight')
For my actual project (which has to handle a dynamic number of legends), I've made it figure out which legend is "longest" and always add that legend last to work around this problem. However, this feels messy and it doesn't allow for adding more legends on other sides of the figure (e.g., I cannot add an x-axis legend below the graph without it getting cut off, since only one legend can be added "last").
Is this an intractable bug in matplotlib, or is there a tidy solution I'm missing?

Hiding axis text in matplotlib plots

I'm trying to plot a figure without tickmarks or numbers on either of the axes (I use axes in the traditional sense, not the matplotlib nomenclature!). An issue I have come across is where matplotlib adjusts the x(y)ticklabels by subtracting a value N, then adds N at the end of the axis.
This may be vague, but the following simplified example highlights the issue, with '6.18' being the offending value of N:
import matplotlib.pyplot as plt
import random
prefix = 6.18
rx = [prefix+(0.001*random.random()) for i in arange(100)]
ry = [prefix+(0.001*random.random()) for i in arange(100)]
plt.plot(rx,ry,'ko')
frame1 = plt.gca()
for xlabel_i in frame1.axes.get_xticklabels():
xlabel_i.set_visible(False)
xlabel_i.set_fontsize(0.0)
for xlabel_i in frame1.axes.get_yticklabels():
xlabel_i.set_fontsize(0.0)
xlabel_i.set_visible(False)
for tick in frame1.axes.get_xticklines():
tick.set_visible(False)
for tick in frame1.axes.get_yticklines():
tick.set_visible(False)
plt.show()
The three things I would like to know are:
How to turn off this behaviour in the first place (although in most cases it is useful, it is not always!) I have looked through matplotlib.axis.XAxis and cannot find anything appropriate
How can I make N disappear (i.e. X.set_visible(False))
Is there a better way to do the above anyway? My final plot would be 4x4 subplots in a figure, if that is relevant.

Instead of hiding each element, you can hide the whole axis:
frame1.axes.get_xaxis().set_visible(False)
frame1.axes.get_yaxis().set_visible(False)
Or, you can set the ticks to an empty list:
frame1.axes.get_xaxis().set_ticks([])
frame1.axes.get_yaxis().set_ticks([])
In this second option, you can still use plt.xlabel() and plt.ylabel() to add labels to the axes.

If you want to hide just the axis text keeping the grid lines:
frame1 = plt.gca()
frame1.axes.xaxis.set_ticklabels([])
frame1.axes.yaxis.set_ticklabels([])
Doing set_visible(False) or set_ticks([]) will also hide the grid lines.

If you are like me and don't always retrieve the axes, ax, when plotting the figure, then a simple solution would be to do
plt.xticks([])
plt.yticks([])

I've colour coded this figure to ease the process.
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
You can have full control over the figure using these commands, to complete the answer I've add also the control over the spines:
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
# X AXIS -BORDER
ax.spines['bottom'].set_visible(False)
# BLUE
ax.set_xticklabels([])
# RED
ax.set_xticks([])
# RED AND BLUE TOGETHER
ax.axes.get_xaxis().set_visible(False)
# Y AXIS -BORDER
ax.spines['left'].set_visible(False)
# YELLOW
ax.set_yticklabels([])
# GREEN
ax.set_yticks([])
# YELLOW AND GREEN TOGHETHER
ax.axes.get_yaxis().set_visible(False)

I was not actually able to render an image without borders or axis data based on any of the code snippets here (even the one accepted at the answer). After digging through some API documentation, I landed on this code to render my image
plt.axis('off')
plt.tick_params(axis='both', left=False, top=False, right=False, bottom=False, labelleft=False, labeltop=False, labelright=False, labelbottom=False)
plt.savefig('foo.png', dpi=100, bbox_inches='tight', pad_inches=0.0)
I used the tick_params call to basically shut down any extra information that might be rendered and I have a perfect graph in my output file.

Somewhat of an old thread but, this seems to be a faster method using the latest version of matplotlib:
set the major formatter for the x-axis
ax.xaxis.set_major_formatter(plt.NullFormatter())

One trick could be setting the color of tick labels as white to hide it!
plt.xticks(color='w')
plt.yticks(color='w')
or to be more generalized (#Armin Okić), you can set it as "None".

When using the object oriented API, the Axes object has two useful methods for removing the axis text, set_xticklabels() and set_xticks().
Say you create a plot using
fig, ax = plt.subplots(1)
ax.plot(x, y)
If you simply want to remove the tick labels, you could use
ax.set_xticklabels([])
or to remove the ticks completely, you could use
ax.set_xticks([])
These methods are useful for specifying exactly where you want the ticks and how you want them labeled. Passing an empty list results in no ticks, or no labels, respectively.

You could simply set xlabel to None, straight in your axis. Below an working example using seaborn
from matplotlib import pyplot as plt
import seaborn as sns
tips = sns.load_dataset("tips")
ax = sns.boxplot(x="day", y="total_bill", data=tips)
ax.set(xlabel=None)
plt.show()

Just do this in case you have subplots
fig, axs = plt.subplots(1, 2, figsize=(16, 8))
ax[0].set_yticklabels([]) # x-axis
ax[0].set_xticklabels([]) # y-axis