I'd like to create a waffle chart in grey shapes for the following dataFrame
data = pd.DataFrame({'Category': ['a', 'b', 'c', 'd'], 'no_occurrence' : [594, 5, 10, 9]})
Here is what I've done so far based on this post
import matplotlib.pyplot as plt
from pywaffle import Waffle
fig = plt.figure(
FigureClass=Waffle,
rows=5,
colors = ('lightgrey', 'black', 'darkgrey', 'lightgrey'),
values=list(data['no_occurrence']/4),
labels=list(data['Category']),
icons = 'sticky-note',
icon_size = 11,
figsize=(12, 8),
icon_legend = True,
legend={'loc': 'lower left','bbox_to_anchor': (0, -0.4), 'ncol': len(data), 'fontsize': 8}
)
As the grey shapes are quite difficult to distinguish, I'd like to hatch the last category (in the figure and the legend) but I can't figure out how to add the hatches in the colors. I have a bar chart with the same categories, where I added hatches, so I'd like to stay consistent.
When using icons as the elements in a waffle chart, internally they are represented as text objects with a special font.
Using patheffects
, hatching can be added, both to the icons in the plot as in the legend.
As you didn't provide toy data, nor an image, I made up some data to show the ideas. As my legend icons are smaller than the icons in the plot, I used a denser hatching for the legend.
import matplotlib.pyplot as plt
from matplotlib import patheffects
import numpy as np
from pywaffle import Waffle
values = [5, 14, 17, 18]
fig = plt.figure(
FigureClass=Waffle,
rows=5,
colors=('lightgrey', 'black', 'darkgrey', 'lightgrey'),
values=values,
labels=[*'abcd'],
icons='sticky-note',
icon_size=60,
figsize=(12, 8),
icon_legend=True,
legend={'loc': 'lower left', 'bbox_to_anchor': (0, -0.4), 'ncol': 4, 'fontsize': 15,
'facecolor': 'white', 'edgecolor': 'black'})
for t in fig.ax.texts[-values[-1]:]:
t.set_path_effects([patheffects.PathPatchEffect(hatch='xxx', fc='lightgrey', ec='white')]) # color='lightgrey')])
fig.ax.legend_.legendHandles[-1].set_path_effects(
[patheffects.PathPatchEffect(hatch='xxxxx', fc='lightgrey', ec='white')])
fig.tight_layout()
plt.show()