Separate halves of split violinplot to compare tail data - matplotlib

Question

Is there a way to physically separate the two halves of a "split" seaborn violinplot (or other type of violinplot)? I'm trying to compare two different treatments, but there is a skinny tail, and it's difficult (impossible) to tell whether one or both halves of the split violin go up all the way to the tip of the tail.
One thought I had was that if the two halves were slightly separated instead of right up next to each other, then it would be easy to absorb the data accurately.
Here is my code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import style
import seaborn as sns
# load data into a dataframe
df1 = pd.read_excel('Modeling analysis charts.xlsx',
sheetname='lmps',
parse_cols=[0,5],
skiprows=0,
header=1)
# identify which dispatch run this data is from
df1['Run']='Scheduling'
# load data into a dataframe
df2 = pd.read_excel('Modeling analysis charts.xlsx',
sheetname='lmps',
parse_cols=[7,12],
skiprows=0,
header=1)
# identify which dispatch run this data is from
df2['Run']='Pricing'
# drop rows with missing data
df1 = df1.dropna(how='any')
df2 = df2.dropna(how='any')
# merge data from different runs
df = pd.concat([df1,df2])
# LMPs are all opposite of actual values, so correct that
df['LMP'] = -df['LMP']
fontsize = 10
style.use('fivethirtyeight')
fig, axes = plt.subplots()
sns.violinplot(x='Scenario', y='LMP', hue='Run', split=True, data=df, inner=None, scale='area', bw=0.2, cut=0, linewidth=0.5, ax = axes)
axes.set_title('Day Ahead Market')
#axes.set_ylim([-15,90])
axes.yaxis.grid(True)
axes.set_xlabel('Scenario')
axes.set_ylabel('LMP ($/MWh)')
#plt.savefig('DAMarket.pdf', bbox_inches='tight')
plt.show()

Answer 1

EDIT: For historical reasons this is the accepted answer, but have a look at #conchoecia more recent and much cleaner implementation.
Cool idea. The basic idea of my implementation is to draw the whole thing, grab the patches corresponding to the two half-violins, and then shift paths of those patches left or right. Code is hopefully self-explanatory, otherwise let me know in the comments.
import numpy as np
import matplotlib.pyplot as plt;
import matplotlib.collections
import seaborn as sns
import pandas as pd
# create some data
n = 10000 # number of samples
c = 5 # classes
y = np.random.randn(n)
x = np.random.randint(0, c, size=n)
z = np.random.rand(n) > 0.5 # sub-class
data = pd.DataFrame(dict(x=x, y=y, z=z))
# initialise new axis;
# if there is random other crap on the axis (e.g. a previous plot),
# the hacky code below won't work
fig, ax = plt.subplots(1,1)
# plot
inner = None # Note: 'box' is default
ax = sns.violinplot(data=data, x='x', y='y', hue='z', split=True, inner=inner, ax=ax)
# offset stuff
delta = 0.02
for ii, item in enumerate(ax.collections):
# axis contains PolyCollections and PathCollections
if isinstance(item, matplotlib.collections.PolyCollection):
# get path
path, = item.get_paths()
vertices = path.vertices
# shift x-coordinates of path
if not inner:
if ii % 2: # -> to right
vertices[:,0] += delta
else: # -> to left
vertices[:,0] -= delta
else: # inner='box' adds another type of PollyCollection
if ii % 3 == 0:
vertices[:,0] -= delta
elif ii % 3 == 1:
vertices[:,0] += delta
else: # ii % 3 = 2
pass

Answer 2

I expanded on #Paul's answer above and made it more robust. It now supports both vertical and horizontal orientation, and I implemented it to work with inner='sticks' since that fits my application.
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.collections
import seaborn as sns
import pandas as pd
def offset_violinplot_halves(ax, delta, width, inner, direction):
"""
This function offsets the halves of a violinplot to compare tails
or to plot something else in between them. This is specifically designed
for violinplots by Seaborn that use the option `split=True`.
For lines, this works on the assumption that Seaborn plots everything with
integers as the center.
Args:
<ax> The axis that contains the violinplots.
<delta> The amount of space to put between the two halves of the violinplot
<width> The total width of the violinplot, as passed to sns.violinplot()
<inner> The type of inner in the seaborn
<direction> Orientation of violinplot. 'hotizontal' or 'vertical'.
Returns:
- NA, modifies the <ax> directly
"""
# offset stuff
if inner == 'sticks':
lines = ax.get_lines()
for line in lines:
if direction == 'horizontal':
data = line.get_ydata()
print(data)
if int(data[0] + 1)/int(data[1] + 1) < 1:
# type is top, move neg, direction backwards for horizontal
data -= delta
else:
# type is bottom, move pos, direction backward for hori
data += delta
line.set_ydata(data)
elif direction == 'vertical':
data = line.get_xdata()
print(data)
if int(data[0] + 1)/int(data[1] + 1) < 1:
# type is left, move neg
data -= delta
else:
# type is left, move pos
data += delta
line.set_xdata(data)
for ii, item in enumerate(ax.collections):
# axis contains PolyCollections and PathCollections
if isinstance(item, matplotlib.collections.PolyCollection):
# get path
path, = item.get_paths()
vertices = path.vertices
half_type = _wedge_dir(vertices, direction)
# shift x-coordinates of path
if half_type in ['top','bottom']:
if inner in ["sticks", None]:
if half_type == 'top': # -> up
vertices[:,1] -= delta
elif half_type == 'bottom': # -> down
vertices[:,1] += delta
elif half_type in ['left', 'right']:
if inner in ["sticks", None]:
if half_type == 'left': # -> left
vertices[:,0] -= delta
elif half_type == 'right': # -> down
vertices[:,0] += delta
def _wedge_dir(vertices, direction):
"""
Args:
<vertices> The vertices from matplotlib.collections.PolyCollection
<direction> Direction must be 'horizontal' or 'vertical' according to how
your plot is laid out.
Returns:
- a string in ['top', 'bottom', 'left', 'right'] that determines where the
half of the violinplot is relative to the center.
"""
if direction == 'horizontal':
result = (direction, len(set(vertices[1:5,1])) == 1)
elif direction == 'vertical':
result = (direction, len(set(vertices[-3:-1,0])) == 1)
outcome_key = {('horizontal', True): 'bottom',
('horizontal', False): 'top',
('vertical', True): 'left',
('vertical', False): 'right'}
# if the first couple x/y values after the start are the same, it
# is the input direction. If not, it is the opposite
return outcome_key[result]
# create some data
n = 100 # number of samples
c = ['cats', 'rats', 'bears', 'pears', 'snares'] # classes
y = np.random.randn(n)
x = np.random.choice(c, size=n)
z = np.random.rand(n) > 0.5 # sub-class
data = pd.DataFrame(dict(x=x, y=y, z=z))
print('done making data')
# initialise new axes;
fig, (ax1, ax2) = plt.subplots(2)
inner = "sticks" # Note: 'box' is default
width = 0.75
delta = 0.05
final_width = width - delta
print(data)
sns.violinplot(data=data, x='y', y='x',
split=True, hue = 'z',
ax = ax1, inner='sticks',
bw = 0.2)
sns.violinplot(data=data, x='x', y='y',
split=True, hue = 'z',
ax = ax2, inner='sticks',
bw = 0.2)
offset_violinplot_halves(ax1, delta, final_width, inner, 'horizontal')
offset_violinplot_halves(ax2, delta, final_width, inner, 'vertical')
plt.show()