Skip to content

Commit ec790d8

Browse files
github-actions[bot]github-actions[bot]
authored
feat(bokeh): implement cat-box-strip (#2768)
## Implementation: `cat-box-strip` - bokeh Implements the **bokeh** version of `cat-box-strip`. **File:** `plots/cat-box-strip/implementations/bokeh.py` --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20601057657)* --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
1 parent 5653eea commit ec790d8

2 files changed

Lines changed: 184 additions & 0 deletions

File tree

‎plots/cat-box-strip/implementations/bokeh.py‎

Lines changed: 157 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,157 @@
1+
""" pyplots.ai
2+
cat-box-strip: Box Plot with Strip Overlay
3+
Library: bokeh 3.8.1 | Python 3.13.11
4+
Quality: 92/100 | Created: 2025-12-30
5+
"""
6+
7+
import numpy as np
8+
import pandas as pd
9+
from bokeh.io import export_png, output_file, save
10+
from bokeh.models import ColumnDataSource, Whisker
11+
from bokeh.plotting import figure
12+
from bokeh.transform import jitter
13+
14+
15+
# Data - Plant growth measurements across different soil types
16+
np.random.seed(42)
17+
18+
categories = ["Sandy", "Clay", "Loamy", "Silty"]
19+
n_per_group = [35, 40, 45, 38]
20+
21+
# Generate data with different distributions per group
22+
data = []
23+
for cat, n in zip(categories, n_per_group, strict=True):
24+
if cat == "Sandy":
25+
values = np.random.normal(25, 6, n) # Lower growth, moderate variance
26+
elif cat == "Clay":
27+
values = np.random.normal(32, 8, n) # Medium growth, high variance
28+
values = np.append(values, [55, 58]) # Add outliers
29+
elif cat == "Loamy":
30+
values = np.random.normal(42, 5, n) # High growth, low variance
31+
else: # Silty
32+
values = np.random.normal(35, 7, n) # Medium-high growth
33+
values = np.append(values, [12, 14]) # Add low outliers
34+
35+
for v in values:
36+
data.append({"category": cat, "value": v})
37+
38+
df = pd.DataFrame(data)
39+
40+
# Calculate box plot statistics for each category
41+
box_data = {"category": [], "q1": [], "q2": [], "q3": [], "upper": [], "lower": []}
42+
43+
for cat in categories:
44+
group = df[df["category"] == cat]["value"]
45+
q1 = group.quantile(0.25)
46+
q2 = group.quantile(0.50)
47+
q3 = group.quantile(0.75)
48+
iqr = q3 - q1
49+
upper_whisker = group[group <= q3 + 1.5 * iqr].max()
50+
lower_whisker = group[group >= q1 - 1.5 * iqr].min()
51+
52+
box_data["category"].append(cat)
53+
box_data["q1"].append(q1)
54+
box_data["q2"].append(q2)
55+
box_data["q3"].append(q3)
56+
box_data["upper"].append(upper_whisker)
57+
box_data["lower"].append(lower_whisker)
58+
59+
box_source = ColumnDataSource(data=box_data)
60+
61+
# Create figure with categorical x-axis
62+
p = figure(
63+
width=4800,
64+
height=2700,
65+
x_range=categories,
66+
title="cat-box-strip · bokeh · pyplots.ai",
67+
x_axis_label="Soil Type",
68+
y_axis_label="Plant Growth (cm)",
69+
tools="",
70+
toolbar_location=None,
71+
)
72+
73+
# Styling - scaled for 4800x2700 canvas
74+
p.title.text_font_size = "36pt"
75+
p.xaxis.axis_label_text_font_size = "28pt"
76+
p.yaxis.axis_label_text_font_size = "28pt"
77+
p.xaxis.major_label_text_font_size = "24pt"
78+
p.yaxis.major_label_text_font_size = "22pt"
79+
p.xaxis.axis_label_standoff = 25
80+
p.yaxis.axis_label_standoff = 25
81+
82+
# Grid styling
83+
p.grid.grid_line_alpha = 0.3
84+
p.grid.grid_line_dash = [6, 4]
85+
p.xgrid.grid_line_color = None
86+
87+
# Background
88+
p.background_fill_color = "#fafafa"
89+
90+
# Draw whiskers using the Whisker annotation
91+
upper_whisker = Whisker(
92+
source=box_source, base="category", upper="upper", lower="q3", line_color="#306998", line_width=2.5
93+
)
94+
upper_whisker.upper_head.size = 30
95+
upper_whisker.upper_head.line_color = "#306998"
96+
upper_whisker.upper_head.line_width = 2.5
97+
upper_whisker.lower_head.size = 0
98+
p.add_layout(upper_whisker)
99+
100+
lower_whisker = Whisker(
101+
source=box_source, base="category", upper="q1", lower="lower", line_color="#306998", line_width=2.5
102+
)
103+
lower_whisker.lower_head.size = 30
104+
lower_whisker.lower_head.line_color = "#306998"
105+
lower_whisker.lower_head.line_width = 2.5
106+
lower_whisker.upper_head.size = 0
107+
p.add_layout(lower_whisker)
108+
109+
# Draw boxes (IQR range) - upper half
110+
p.vbar(
111+
x="category",
112+
top="q3",
113+
bottom="q2",
114+
width=0.5,
115+
source=box_source,
116+
fill_color="#306998",
117+
fill_alpha=0.4,
118+
line_color="#306998",
119+
line_width=3,
120+
)
121+
122+
# Draw boxes (IQR range) - lower half
123+
p.vbar(
124+
x="category",
125+
top="q2",
126+
bottom="q1",
127+
width=0.5,
128+
source=box_source,
129+
fill_color="#306998",
130+
fill_alpha=0.4,
131+
line_color="#306998",
132+
line_width=3,
133+
)
134+
135+
# Median line (horizontal segment across the box)
136+
p.segment(x0="category", x1="category", y0="q2", y1="q2", source=box_source, line_color="#1a3d5c", line_width=4)
137+
138+
# Strip plot overlay with jitter
139+
strip_source = ColumnDataSource(data={"category": df["category"], "value": df["value"]})
140+
141+
p.scatter(
142+
x=jitter("category", width=0.3, range=p.x_range),
143+
y="value",
144+
source=strip_source,
145+
size=16,
146+
fill_color="#FFD43B",
147+
fill_alpha=0.75,
148+
line_color="#b8860b",
149+
line_width=2,
150+
)
151+
152+
# Save PNG
153+
export_png(p, filename="plot.png")
154+
155+
# Save HTML for interactive version
156+
output_file("plot.html")
157+
save(p)

‎plots/cat-box-strip/metadata/bokeh.yaml‎

Lines changed: 27 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,27 @@
1+
library: bokeh
2+
specification_id: cat-box-strip
3+
created: '2025-12-30T16:31:45Z'
4+
updated: '2025-12-30T16:44:16Z'
5+
generated_by: claude-opus-4-5-20251101
6+
workflow_run: 20601057657
7+
issue: 0
8+
python_version: 3.13.11
9+
library_version: 3.8.1
10+
preview_url: https://storage.googleapis.com/pyplots-images/plots/cat-box-strip/bokeh/plot.png
11+
preview_thumb: https://storage.googleapis.com/pyplots-images/plots/cat-box-strip/bokeh/plot_thumb.png
12+
preview_html: https://storage.googleapis.com/pyplots-images/plots/cat-box-strip/bokeh/plot.html
13+
quality_score: 92
14+
review:
15+
strengths:
16+
- Excellent manual box plot construction using Bokeh primitives (Whisker, vbar,
17+
segment)
18+
- Good use of jitter transform for strip points to reduce overlap
19+
- Proper colorblind-safe color scheme (blue/yellow contrast)
20+
- Well-calculated IQR-based whiskers with proper outlier handling
21+
- Clear demonstration of different distributions and outliers across categories
22+
- Font sizes properly scaled for 4800x2700 canvas
23+
weaknesses:
24+
- No legend explaining what box/strip elements represent (minor for this plot type)
25+
- Could add HoverTool to show exact values on hover for the HTML version
26+
- The median line segment has zero width (x0=x1) which works but is technically
27+
a point not a line

0 commit comments

Comments
 (0)