feat(plotnine): implement swarm-basic (#9938)

## Implementation: `swarm-basic` - python/plotnine

Implements the **python/plotnine** version of `swarm-basic`.

**File:** `plots/swarm-basic/implementations/python/plotnine.py`

**Parent Issue:** #974

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/30192131037)*

---------

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

Author: github-actions[bot]

plots/swarm-basic/implementations/python/plotnine.py

@@ -1,7 +1,7 @@
 """ anyplot.ai
 swarm-basic: Basic Swarm Plot
-Library: plotnine 0.15.3 | Python 3.13.13
-Quality: 87/100 | Updated: 2026-05-05
+Library: plotnine 0.15.7 | Python 3.13.14
+Quality: 89/100 | Updated: 2026-07-26
 """
 
 import sys
@@ -15,15 +15,16 @@
 import pandas as pd
 from plotnine import (
     aes,
+    element_blank,
     element_line,
     element_rect,
     element_text,
+    geom_line,
     geom_point,
     ggplot,
     labs,
-    position_jitter,
     scale_color_manual,
-    stat_summary,
+    scale_x_continuous,
     theme,
     theme_minimal,
 )
@@ -55,28 +56,77 @@
 
 df = pd.DataFrame(data, columns=["treatment", "biomarker"])
 df["treatment"] = pd.Categorical(df["treatment"], categories=treatment_groups, ordered=True)
+df["x_num"] = df["treatment"].cat.codes.astype(float)
+
+
+# Deterministic beeswarm packing: sweep points in ascending value order and
+# place each one in the nearest-to-center offset slot (alternating sides)
+# whose most recent occupant already cleared a minimum vertical gap — a slot
+# only frees up once its last point is far enough below the new one, so
+# offsets keep growing in dense stretches instead of every sparse column
+# resetting back to center and stacking near-concentrically with its neighbor.
+# min_gap is fixed to the shared y-axis scale (not each group's own spread)
+# since the marker's on-canvas footprint is the same regardless of group.
+def beeswarm_offsets(values, min_gap, spacing=0.09):
+    offsets = np.zeros(len(values))
+    slot_last_y = {}  # offset slot (int) -> value of the last point placed there
+    for idx in np.argsort(values):
+        y = values[idx]
+        step = 0
+        while True:
+            for slot in (0,) if step == 0 else (step, -step):
+                last_y = slot_last_y.get(slot)
+                if last_y is None or y - last_y >= min_gap:
+                    offsets[idx] = slot * spacing
+                    slot_last_y[slot] = y
+                    step = None
+                    break
+            if step is None:
+                break
+            step += 1
+    return offsets
+
+
+swarm_min_gap = (df["biomarker"].max() - df["biomarker"].min()) * 0.05
+for group in treatment_groups:
+    mask = df["treatment"] == group
+    df.loc[mask, "x_num"] += beeswarm_offsets(df.loc[mask, "biomarker"].to_numpy(), swarm_min_gap)
+
+medians_df = df.groupby("treatment", observed=True)["biomarker"].median().reset_index()
+medians_df["x_num"] = medians_df["treatment"].cat.codes.astype(float)
 
 # Plot
 plot = (
-    ggplot(df, aes(x="treatment", y="biomarker", color="treatment"))
-    + geom_point(position=position_jitter(width=0.3, height=0, random_state=42), size=3.5, alpha=0.75)
-    + stat_summary(fun_y=np.median, geom="point", size=8, shape="D", color=INK)
+    ggplot(df, aes(x="x_num", y="biomarker", color="treatment"))
+    + geom_point(size=2.2, alpha=0.75)
+    + geom_line(
+        medians_df,
+        aes(x="x_num", y="biomarker", group=1),
+        linetype="dashed",
+        color=INK_SOFT,
+        size=1.0,
+        inherit_aes=False,
+    )
+    + geom_point(medians_df, aes(x="x_num", y="biomarker"), size=6, shape="D", color=INK, inherit_aes=False)
     + scale_color_manual(values=IMPRINT)
+    + scale_x_continuous(breaks=list(range(len(treatment_groups))), labels=treatment_groups)
     + labs(x="Treatment Group", y="Biomarker Level (ng/mL)", title="swarm-basic · plotnine · anyplot.ai")
     + theme_minimal()
     + theme(
-        figure_size=(16, 9),
-        text=element_text(size=14),
+        figure_size=(8, 4.5),
+        text=element_text(size=7),
         plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
         panel_background=element_rect(fill=PAGE_BG),
+        panel_border=element_blank(),
         panel_grid_major=element_line(color=INK, size=0.3, alpha=0.08),
         panel_grid_minor=element_line(color=INK, size=0.2, alpha=0.04),
-        axis_title=element_text(color=INK, size=20),
-        axis_text=element_text(color=INK_SOFT, size=16),
-        plot_title=element_text(color=INK, size=24),
+        axis_ticks_major=element_blank(),
+        axis_title=element_text(color=INK, size=10),
+        axis_text=element_text(color=INK_SOFT, size=8),
+        plot_title=element_text(color=INK, size=13),
         legend_position="none",
     )
 )
 
 # Save
-plot.save(f"plot-{THEME}.png", dpi=300)
+plot.save(f"plot-{THEME}.png", dpi=400, width=8, height=4.5, units="in")