feat(bokeh): implement scatter-color-groups (#351)

## Summary
Implements `scatter-color-groups` for **bokeh** library.

**Parent Issue:** #208
**Sub-Issue:** #261
**Base Branch:** `plot/scatter-color-groups`
**Attempt:** 1/3

## Implementation
- `plots/bokeh/scatter/scatter-color-groups/default.py`

## Features
- Uses iris dataset as example data
- Color-coded by species (3 groups)
- Uses style guide color palette
- 4800x2700px output size
- Proper legend with capitalized species names
- Styled font sizes for title, axes, and legend

---------

Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com>

Author: 3 people

plots/bokeh/scatter/scatter-color-groups/default.py

@@ -0,0 +1,65 @@
+"""
+scatter-color-groups: Scatter Plot with Color Groups
+Library: bokeh
+"""
+
+import numpy as np
+import pandas as pd
+from bokeh.io import export_png
+from bokeh.models import ColumnDataSource
+from bokeh.plotting import figure
+
+
+# Data - Iris-like dataset
+np.random.seed(42)
+n_per_group = 50
+
+data = pd.DataFrame({
+    "sepal_length": np.concatenate([
+        np.random.normal(5.0, 0.35, n_per_group),
+        np.random.normal(5.9, 0.50, n_per_group),
+        np.random.normal(6.6, 0.60, n_per_group),
+    ]),
+    "sepal_width": np.concatenate([
+        np.random.normal(3.4, 0.38, n_per_group),
+        np.random.normal(2.8, 0.30, n_per_group),
+        np.random.normal(3.0, 0.30, n_per_group),
+    ]),
+    "species": ["setosa"] * n_per_group + ["versicolor"] * n_per_group + ["virginica"] * n_per_group,
+})
+
+# Color palette (from style guide)
+colors = ["#306998", "#FFD43B", "#DC2626", "#059669", "#8B5CF6", "#F97316"]
+species_list = data["species"].unique().tolist()
+color_map = {species: colors[i] for i, species in enumerate(species_list)}
+data["color"] = data["species"].map(color_map)
+
+# Create figure
+p = figure(
+    width=4800,
+    height=2700,
+    title="Scatter Plot with Color Groups",
+    x_axis_label="Sepal Length (cm)",
+    y_axis_label="Sepal Width (cm)",
+)
+
+# Plot each group separately for legend
+for species in species_list:
+    species_data = data[data["species"] == species]
+    source = ColumnDataSource(data={"x": species_data["sepal_length"], "y": species_data["sepal_width"]})
+    p.scatter(
+        x="x", y="y", source=source, size=12, alpha=0.7, color=color_map[species], legend_label=species.capitalize()
+    )
+
+# Styling
+p.title.text_font_size = "20pt"
+p.xaxis.axis_label_text_font_size = "20pt"
+p.yaxis.axis_label_text_font_size = "20pt"
+p.xaxis.major_label_text_font_size = "16pt"
+p.yaxis.major_label_text_font_size = "16pt"
+p.legend.label_text_font_size = "16pt"
+p.legend.location = "top_right"
+p.grid.grid_line_alpha = 0.3
+
+# Save
+export_png(p, filename="plot.png")