fix(letsplot): address review feedback for line-retention-cohort

Attempt 1/3 - fixes based on AI review

Author: github-actions[bot]

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

@@ -1,4 +1,4 @@
-""" pyplots.ai
+"""pyplots.ai
 line-retention-cohort: User Retention Curve by Cohort
 Library: letsplot 4.9.0 | Python 3.14.3
 Quality: 85/100 | Created: 2026-03-16
@@ -36,29 +36,69 @@
 
 df = pd.DataFrame(rows)
 
-# Colors: cohesive palette starting with Python Blue, older cohorts lighter
-colors = ["#93B5C9", "#7EAAB8", "#5590A3", "#306998", "#1B4965"]
+# Endpoint labels: last data point per cohort, with nudge to avoid overlap
+endpoints = df[df["Week"] == 12].copy()
+endpoints["label"] = endpoints["Retention"].apply(lambda x: f"{x:.0f}%")
+# Adjust y positions to prevent label overlap (spread close values apart)
+sorted_ep = endpoints.sort_values("Retention").reset_index(drop=True)
+min_gap = 3.5
+for i in range(1, len(sorted_ep)):
+    if sorted_ep.loc[i, "Retention"] - sorted_ep.loc[i - 1, "Retention"] < min_gap:
+        sorted_ep.loc[i, "Retention"] = sorted_ep.loc[i - 1, "Retention"] + min_gap
+endpoints = sorted_ep
+
+# Colorblind-friendly palette with distinct hues (oldest=lightest, newest=boldest)
+colors = ["#A6CEE3", "#B2DF8A", "#FDBF6F", "#E31A1C", "#306998"]
+
+# Line widths: older cohorts thinner, newer cohorts bolder
+line_widths = [1.5, 1.8, 2.0, 2.5, 3.0]
+
+# Build plot with per-cohort layers for varying line widths
+cohort_labels = df["Cohort"].unique().tolist()
+
+plot = ggplot()
+
+# Add lines and points per cohort with distinct widths
+for i, cohort_label in enumerate(cohort_labels):
+    cdf = df[df["Cohort"] == cohort_label]
+    plot = plot + geom_line(
+        aes(x="Week", y="Retention", color="Cohort"),
+        data=cdf,
+        size=line_widths[i],
+        alpha=0.9,
+        tooltips=layer_tooltips().line("@Cohort").line("Week @Week").line("Retention @Retention{.1f}%"),
+    )
 
-# Plot
 plot = (
-    ggplot(df, aes(x="Week", y="Retention", color="Cohort"))
-    + geom_line(size=2.5, alpha=0.9)
-    + geom_point(size=4, alpha=0.85)
-    + geom_hline(yintercept=20, linetype="dashed", color="#888888", size=1)
+    plot
+    + geom_point(aes(x="Week", y="Retention", color="Cohort"), data=df, size=4, alpha=0.85)
+    + geom_hline(yintercept=20, linetype="dashed", color="#999999", size=0.8)
+    + geom_text(
+        aes(x="Week", y="Retention", label="label", color="Cohort"), data=endpoints, size=14, nudge_x=0.6, hjust=0
+    )
+    + geom_text(
+        aes(x="x", y="y", label="label"),
+        data=pd.DataFrame({"x": [0.2], "y": [20], "label": ["20% threshold"]}),
+        size=12,
+        color="#999999",
+        hjust=0,
+        vjust=-1.2,
+    )
     + scale_color_manual(values=colors)
-    + scale_x_continuous(breaks=list(range(0, 13, 2)))
+    + scale_x_continuous(breaks=list(range(0, 13, 2)), limits=[0, 14.5])
     + scale_y_continuous(breaks=list(range(0, 101, 20)), limits=[0, 105])
     + labs(title="line-retention-cohort · letsplot · pyplots.ai", x="Weeks Since Signup", y="Retained Users (%)")
     + theme_minimal()
     + theme(
-        plot_title=element_text(size=28, hjust=0.5),
+        plot_title=element_text(size=28, hjust=0.5, face="bold"),
         axis_title=element_text(size=22),
         axis_text=element_text(size=18),
         legend_title=element_blank(),
         legend_text=element_text(size=16),
         legend_position="right",
-        panel_grid_major=element_line(color="#E0E0E0", size=0.5),
+        panel_grid_major=element_line(color="#EBEBEB", size=0.4),
         panel_grid_minor=element_blank(),
+        plot_background=element_rect(color="white", fill="white"),
     )
     + ggsize(1600, 900)
 )