feat(plotnine): implement errorbar-basic (#9521)

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

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

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

**Parent Issue:** #973

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/28473397165)*

---------

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/errorbar-basic/implementations/python/plotnine.py

@@ -1,7 +1,7 @@
 """ anyplot.ai
 errorbar-basic: Basic Error Bar Plot
-Library: plotnine 0.15.3 | Python 3.14.4
-Quality: 85/100 | Updated: 2026-04-25
+Library: plotnine 0.15.7 | Python 3.13.14
+Quality: 84/100 | Updated: 2026-06-30
 """
 
 import os
@@ -13,12 +13,13 @@
     element_line,
     element_rect,
     element_text,
-    geom_errorbar,
-    geom_point,
+    geom_crossbar,
     ggplot,
     labs,
     position_dodge,
     scale_color_manual,
+    scale_fill_manual,
+    scale_x_discrete,
     theme,
     theme_minimal,
 )
@@ -29,76 +30,83 @@
 ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
 INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
 INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
+INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
 
 IMPRINT = ["#009E73", "#C475FD", "#4467A3"]
 
-# Data — three lab methods measured across six samples
+# Data — three analytical methods measuring nitrate concentration across six sampling sites
 data = pd.DataFrame(
     {
-        "sample": [
-            "Sample A",
-            "Sample B",
-            "Sample C",
-            "Sample D",
-            "Sample E",
-            "Sample F",
-            "Sample A",
-            "Sample B",
-            "Sample C",
-            "Sample D",
-            "Sample E",
-            "Sample F",
-            "Sample A",
-            "Sample B",
-            "Sample C",
-            "Sample D",
-            "Sample E",
-            "Sample F",
-        ],
-        "method": (["Method A"] * 6 + ["Method B"] * 6 + ["Method C"] * 6),
-        "measurement": [
-            42.5,
-            38.2,
-            55.1,
-            47.8,
-            33.6,
-            51.3,
-            44.8,
-            40.1,
-            53.6,
+        "site": ["Site A", "Site B", "Site C", "Site D", "Site E", "Site F"] * 3,
+        "method": ["Standard"] * 6 + ["Enhanced"] * 6 + ["Automated"] * 6,
+        "concentration": [
+            # Standard: baseline sensitivity, tight precision
+            36.2,
+            39.8,
+            42.1,
+            37.5,
+            43.6,
+            40.4,
+            # Enhanced: ~35% higher detection
+            48.5,
+            52.3,
+            55.7,
             49.2,
-            35.9,
-            52.7,
-            41.2,
-            39.5,
-            56.3,
-            46.4,
-            34.8,
-            50.1,
+            56.1,
+            51.8,
+            # Automated: highest values, greatest variability
+            61.4,
+            65.8,
+            69.2,
+            58.6,
+            67.3,
+            63.5,
+        ],
+        "se": [
+            1.8,
+            2.1,
+            1.6,
+            2.3,
+            1.9,
+            2.0,  # Standard: SE ±1.6–2.3
+            3.2,
+            2.8,
+            3.5,
+            3.0,
+            2.6,
+            3.4,  # Enhanced: SE ±2.6–3.5
+            5.1,
+            6.3,
+            4.8,
+            7.2,
+            5.5,
+            6.0,  # Automated: SE ±4.8–7.2
         ],
-        "error": [3.2, 4.1, 2.8, 5.5, 3.8, 4.2, 2.6, 3.4, 3.1, 4.2, 3.0, 3.6, 3.9, 4.5, 2.5, 5.1, 4.3, 4.0],
     }
 )
 
-data["ymin"] = data["measurement"] - data["error"]
-data["ymax"] = data["measurement"] + data["error"]
+data["ymin"] = data["concentration"] - data["se"]
+data["ymax"] = data["concentration"] + data["se"]
+
+# Sort sites by Standard-method concentration so all three methods trend upward left→right
+site_order = data[data["method"] == "Standard"].set_index("site")["concentration"].sort_values().index.tolist()
 
-# Order samples by mean measurement to create visual hierarchy
-sample_order = data.groupby("sample")["measurement"].mean().sort_values().index.tolist()
-data["sample"] = pd.Categorical(data["sample"], categories=sample_order, ordered=True)
+dodge = position_dodge(width=0.6)
 
-dodge = position_dodge(width=0.55)
+title = "errorbar-basic · python · plotnine · anyplot.ai"
+subtitle = "Automated sampling shows 3–4× wider uncertainty than Standard across all sites"
 
 plot = (
-    ggplot(data, aes(x="sample", y="measurement", color="method", group="method"))
-    + geom_errorbar(aes(ymin="ymin", ymax="ymax"), width=0.35, size=1.4, position=dodge)
-    + geom_point(size=5, position=dodge)
+    ggplot(data, aes(x="site", y="concentration", color="method", fill="method", group="method"))
+    + geom_crossbar(aes(ymin="ymin", ymax="ymax"), width=0.18, fatten=3, size=0.9, alpha=0.2, position=dodge)
     + scale_color_manual(values=IMPRINT, name="Method")
-    + labs(x="Experimental Sample", y="Measurement Value (mg/L)", title="errorbar-basic · plotnine · anyplot.ai")
+    + scale_fill_manual(values=IMPRINT, name="Method")
+    + scale_x_discrete(limits=site_order)
+    + labs(x="Sampling Site", y="Nitrate Concentration (mg/L)", title=title, subtitle=subtitle)
     + theme_minimal()
     + theme(
-        figure_size=(16, 9),
-        text=element_text(size=14, color=INK_SOFT),
+        figure_size=(8, 4.5),
+        text=element_text(size=7, color=INK_SOFT),
         plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
         panel_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
         panel_border=element_blank(),
@@ -108,15 +116,16 @@
         axis_line_x=element_line(color=INK_SOFT, size=0.6),
         axis_line_y=element_blank(),
         axis_ticks=element_blank(),
-        axis_title=element_text(size=20, color=INK),
-        axis_text=element_text(size=16, color=INK_SOFT),
-        plot_title=element_text(size=24, color=INK, weight="bold"),
-        legend_background=element_rect(fill=ELEVATED_BG, color=ELEVATED_BG),
+        axis_title=element_text(size=10, color=INK),
+        axis_text=element_text(size=8, color=INK_SOFT),
+        plot_title=element_text(size=12, color=INK, weight="bold"),
+        plot_subtitle=element_text(size=9, color=INK_MUTED),
+        legend_background=element_rect(fill=ELEVATED_BG, color=INK_SOFT, size=0.4),
         legend_key=element_rect(fill=PAGE_BG, color=PAGE_BG),
-        legend_text=element_text(size=16, color=INK_SOFT),
-        legend_title=element_text(size=16, color=INK),
+        legend_text=element_text(size=8, color=INK_SOFT),
+        legend_title=element_text(size=8, color=INK),
         legend_position="right",
     )
 )
 
-plot.save(f"plot-{THEME}.png", dpi=300, width=16, height=9, verbose=False)
+plot.save(f"plot-{THEME}.png", dpi=400, width=8, height=4.5, units="in", verbose=False)