feat(plotnine): implement line-retention-cohort

Author: github-actions[bot]

plots/line-retention-cohort/implementations/plotnine.py

@@ -0,0 +1,101 @@
+"""pyplots.ai
+line-retention-cohort: User Retention Curve by Cohort
+Library: plotnine | Python 3.13
+Quality: pending | Created: 2026-03-16
+"""
+
+import numpy as np
+import pandas as pd
+from plotnine import (
+    aes,
+    annotate,
+    element_blank,
+    element_line,
+    element_text,
+    geom_hline,
+    geom_line,
+    geom_point,
+    ggplot,
+    labs,
+    scale_alpha_identity,
+    scale_color_manual,
+    scale_x_continuous,
+    scale_y_continuous,
+    theme,
+    theme_minimal,
+)
+
+
+# Data
+np.random.seed(42)
+
+cohorts = {
+    "Jan 2025": {"size": 1245, "decay": 0.18},
+    "Feb 2025": {"size": 1102, "decay": 0.16},
+    "Mar 2025": {"size": 1380, "decay": 0.14},
+    "Apr 2025": {"size": 1290, "decay": 0.12},
+    "May 2025": {"size": 1455, "decay": 0.10},
+}
+
+weeks = np.arange(0, 13)
+rows = []
+
+for cohort_name, info in cohorts.items():
+    retention = 100 * np.exp(-info["decay"] * weeks)
+    noise = np.concatenate(([0], np.cumsum(np.random.normal(0, 0.8, len(weeks) - 1))))
+    retention = np.clip(retention + noise, 0, 100)
+    retention[0] = 100.0
+    label = f"{cohort_name} (n={info['size']:,})"
+    for w, r in zip(weeks, retention, strict=True):
+        rows.append({"week": w, "retention": r, "cohort": label})
+
+df = pd.DataFrame(rows)
+
+cohort_labels = list(df["cohort"].unique())
+df["cohort"] = pd.Categorical(df["cohort"], categories=cohort_labels, ordered=True)
+
+alpha_map = dict(zip(cohort_labels, [0.45, 0.55, 0.65, 0.80, 1.0], strict=True))
+df["line_alpha"] = df["cohort"].map(alpha_map).astype(float)
+
+# Colors
+colors = ["#8FADC2", "#7A9AB5", "#306998", "#E8783A", "#D4522A"]
+
+# Plot
+plot = (
+    ggplot(df, aes(x="week", y="retention", color="cohort", group="cohort"))
+    + geom_hline(yintercept=20, linetype="dashed", color="#AAAAAA", size=0.6)
+    + geom_line(aes(alpha="line_alpha"), size=1.5)
+    + scale_alpha_identity()
+    + geom_point(aes(alpha="line_alpha"), size=2.5)
+    + scale_color_manual(values=colors)
+    + scale_x_continuous(breaks=range(0, 13), labels=[str(w) for w in range(0, 13)])
+    + scale_y_continuous(
+        limits=(0, 105), breaks=[0, 20, 40, 60, 80, 100], labels=["0%", "20%", "40%", "60%", "80%", "100%"]
+    )
+    + annotate("text", x=12.3, y=22.5, label="20% threshold", size=9, color="#999999", ha="right")
+    + labs(
+        x="Weeks Since Signup",
+        y="Retained Users",
+        color="Cohort",
+        title="line-retention-cohort · plotnine · pyplots.ai",
+    )
+    + theme_minimal()
+    + theme(
+        figure_size=(16, 9),
+        text=element_text(size=14),
+        plot_title=element_text(size=24, weight="bold"),
+        axis_title=element_text(size=20),
+        axis_text=element_text(size=16),
+        legend_title=element_text(size=18),
+        legend_text=element_text(size=14),
+        legend_position="right",
+        panel_grid_major_x=element_blank(),
+        panel_grid_minor=element_blank(),
+        panel_grid_major_y=element_line(color="#E0E0E0", size=0.5, alpha=0.5),
+        axis_line_x=element_line(color="#333333", size=0.5),
+        axis_line_y=element_line(color="#333333", size=0.5),
+    )
+)
+
+# Save
+plot.save("plot.png", dpi=300, verbose=False)