Improve subplot size/spacing with many subplots in matplotlib
PythonPandasMatplotlibSeabornSubplotPython Problem Overview
Very similar to this question but with the difference that my figure can be as large as it needs to be.
I need to generate a whole bunch of vertically-stacked plots in matplotlib. The result will be saved using figsave and viewed on a webpage, so I don't care how tall the final image is as long as the subplots are spaced so they don't overlap.
No matter how big I allow the figure to be, the subplots always seem to overlap.
My code currently looks like
import matplotlib.pyplot as plt
import my_other_module
titles, x_lists, y_lists = my_other_module.get_data()
fig = plt.figure(figsize=(10,60))
for i, y_list in enumerate(y_lists):
plt.subplot(len(titles), 1, i)
plt.xlabel("Some X label")
plt.ylabel("Some Y label")
plt.title(titles[i])
plt.plot(x_lists[i],y_list)
fig.savefig('out.png', dpi=100)
Python Solutions
Solution 1 - Python
Try using plt.tight_layout
As a quick example:
import matplotlib.pyplot as plt
fig, axes = plt.subplots(nrows=4, ncols=4)
fig.tight_layout() # Or equivalently, "plt.tight_layout()"
plt.show()
Without Tight Layout
With Tight Layout
Solution 2 - Python
You can use plt.subplots_adjust
to change the spacing between the subplots (source)
call signature:
subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=None, hspace=None)
The parameter meanings (and suggested defaults) are:
left = 0.125 # the left side of the subplots of the figure
right = 0.9 # the right side of the subplots of the figure
bottom = 0.1 # the bottom of the subplots of the figure
top = 0.9 # the top of the subplots of the figure
wspace = 0.2 # the amount of width reserved for blank space between subplots
hspace = 0.2 # the amount of height reserved for white space between subplots
The actual defaults are controlled by the rc file
Solution 3 - Python
I found that subplots_adjust(hspace = 0.001) is what ended up working for me. When I use space = None, there is still white space between each plot. Setting it to something very close to zero however seems to force them to line up. What I've uploaded here isn't the most elegant piece of code, but you can see how the hspace works.
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as tic
fig = plt.figure()
x = np.arange(100)
y = 3.*np.sin(x*2.*np.pi/100.)
for i in range(5):
temp = 510 + i
ax = plt.subplot(temp)
plt.plot(x,y)
plt.subplots_adjust(hspace = .001)
temp = tic.MaxNLocator(3)
ax.yaxis.set_major_locator(temp)
ax.set_xticklabels(())
ax.title.set_visible(False)
plt.show()
Solution 4 - Python
Similar to tight_layout
matplotlib now (as of version 2.2) provides constrained_layout
. In contrast to tight_layout
, which may be called any time in the code for a single optimized layout, constrained_layout
is a property, which may be active and will optimze the layout before every drawing step.
Hence it needs to be activated before or during subplot creation, such as figure(constrained_layout=True)
or subplots(constrained_layout=True)
.
Example:
import matplotlib.pyplot as plt
fig, axes = plt.subplots(4,4, constrained_layout=True)
plt.show()
constrained_layout may as well be set via rcParams
plt.rcParams['figure.constrained_layout.use'] = True
See the what's new entry and the Constrained Layout Guide
Solution 5 - Python
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(10,60))
plt.subplots_adjust( ... )
The plt.subplots_adjust method:
def subplots_adjust(*args, **kwargs):
"""
call signature::
subplots_adjust(left=None, bottom=None, right=None, top=None,
wspace=None, hspace=None)
Tune the subplot layout via the
:class:`matplotlib.figure.SubplotParams` mechanism. The parameter
meanings (and suggested defaults) are::
left = 0.125 # the left side of the subplots of the figure
right = 0.9 # the right side of the subplots of the figure
bottom = 0.1 # the bottom of the subplots of the figure
top = 0.9 # the top of the subplots of the figure
wspace = 0.2 # the amount of width reserved for blank space between subplots
hspace = 0.2 # the amount of height reserved for white space between subplots
The actual defaults are controlled by the rc file
"""
fig = gcf()
fig.subplots_adjust(*args, **kwargs)
draw_if_interactive()
or
fig = plt.figure(figsize=(10,60))
fig.subplots_adjust( ... )
The size of the picture matters.
"I've tried messing with hspace, but increasing it only seems to make all of the graphs smaller without resolving the overlap problem."
Thus to make more white space and keep the sub plot size the total image needs to be bigger.
Solution 6 - Python
You could try the subplot_tool()
plt.subplot_tool()
Solution 7 - Python
- Resolving this issue when plotting a dataframe with
pandas.DataFrame.plot
, which usesmatplotlib
as the default backend.- The following works for whichever
kind=
is specified (e.g.'bar'
,'scatter'
,'hist'
, etc.)
- The following works for whichever
- Tested in
python 3.8.12
,pandas 1.3.4
,matplotlib 3.4.3
Imports and sample data
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
# sinusoidal sample data
sample_length = range(1, 15+1)
rads = np.arange(0, 2*np.pi, 0.01)
data = np.array([np.sin(t*rads) for t in sample_length])
df = pd.DataFrame(data.T, index=pd.Series(rads.tolist(), name='radians'), columns=[f'freq: {i}x' for i in sample_length])
# display(df.head(3))
freq: 1x freq: 2x freq: 3x freq: 4x freq: 5x freq: 6x freq: 7x freq: 8x freq: 9x freq: 10x freq: 11x freq: 12x freq: 13x freq: 14x freq: 15x
radians
0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.01 0.010000 0.019999 0.029996 0.039989 0.049979 0.059964 0.069943 0.079915 0.089879 0.099833 0.109778 0.119712 0.129634 0.139543 0.149438
0.02 0.019999 0.039989 0.059964 0.079915 0.099833 0.119712 0.139543 0.159318 0.179030 0.198669 0.218230 0.237703 0.257081 0.276356 0.295520
# default plot with subplots; each column is a subplot
axes = df.plot(subplots=True)
Adjust the Spacing
- Adjust the default parameters in
pandas.DataFrame.plot
- Change
figsize
: a width of 5 and a height of 4 for each subplot is a good place to start - Change
layout
: (rows, columns) for the layout of subplots. sharey=True
andsharex=True
so space isn't taken for redundant labels on each subplot.
- Change
- The
.plot
method returns a numpy array ofmatplotlib.axes.Axes
, which should be flattened to easily work with. - Use
.get_figure()
to extract theDataFrame.plot
figure object from one of theAxes
. - Use
fig.tight_layout()
if desired.
axes = df.plot(subplots=True, layout=(3, 5), figsize=(25, 16), sharex=True, sharey=True)
# flatten the axes array to easily access any subplot
axes = axes.flat
# extract the figure object
fig = axes[0].get_figure()
# use tight_layout
fig.tight_layout()