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fix(altair): address review feedback for line-retention-cohort
Attempt 1/3 - fixes based on AI review
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  • plots/line-retention-cohort/implementations

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

Lines changed: 86 additions & 53 deletions
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
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""" pyplots.ai
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"""pyplots.ai
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line-retention-cohort: User Retention Curve by Cohort
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Library: altair 6.0.0 | Python 3.14.3
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Quality: 84/100 | Created: 2026-03-16
@@ -13,11 +13,11 @@
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np.random.seed(42)
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cohorts = {
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"Jan 2025": {"size": 1245, "half_life": 3.5},
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"Feb 2025": {"size": 1102, "half_life": 4.0},
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"Mar 2025": {"size": 1380, "half_life": 4.8},
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"Apr 2025": {"size": 1510, "half_life": 5.5},
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"May 2025": {"size": 1423, "half_life": 6.2},
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"Jan 2025": {"size": 1245, "half_life": 3.5, "order": 0},
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"Feb 2025": {"size": 1102, "half_life": 4.0, "order": 1},
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"Mar 2025": {"size": 1380, "half_life": 4.8, "order": 2},
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"Apr 2025": {"size": 1510, "half_life": 5.5, "order": 3},
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"May 2025": {"size": 1423, "half_life": 6.2, "order": 4},
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}
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weeks = np.arange(0, 13)
@@ -29,77 +29,110 @@
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retention[0] = 100.0
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legend_label = f"{cohort_label} (n={info['size']:,})"
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for w, r in zip(weeks, retention, strict=True):
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rows.append({"Week": w, "Retention (%)": round(r, 1), "Cohort": legend_label})
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rows.append({"Week": w, "Retention (%)": round(r, 1), "Cohort": legend_label, "order": info["order"]})
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df = pd.DataFrame(rows)
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# Colors - Python Blue first, cohesive palette for 5 cohorts
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colors = ["#306998", "#E15759", "#59A14F", "#EDC948", "#B07AA1"]
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# Colorblind-safe palette: blue → teal → amber → orange → deep blue
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# Avoids red-green distinction, uses luminance + hue variation
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colors = ["#88CCEE", "#44AA99", "#DDCC77", "#CC6677", "#332288"]
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cohort_labels = [f"{c} (n={info['size']:,})" for c, info in cohorts.items()]
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# Graduated opacity and stroke width: older cohorts fade, newer ones pop
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opacity_map = {0: 0.35, 1: 0.50, 2: 0.65, 3: 0.80, 4: 1.0}
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width_map = {0: 1.5, 1: 2.0, 2: 2.5, 3: 3.0, 4: 4.0}
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# Interactive highlight on hover
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highlight = alt.selection_point(fields=["Cohort"], on="pointerover", empty=False)
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# Lines - newer cohorts are thicker/more opaque
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lines = (
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alt.Chart(df)
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.mark_line()
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.encode(
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x=alt.X(
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"Week:Q",
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title="Weeks Since Signup",
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scale=alt.Scale(domain=[0, 12]),
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axis=alt.Axis(labelFontSize=18, titleFontSize=22, tickMinStep=1),
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),
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y=alt.Y(
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"Retention (%):Q",
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title="Retention (%)",
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scale=alt.Scale(domain=[0, 100]),
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axis=alt.Axis(labelFontSize=18, titleFontSize=22, format=".0f"),
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),
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color=alt.Color(
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"Cohort:N",
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scale=alt.Scale(domain=cohort_labels, range=colors),
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legend=alt.Legend(title="Cohort", titleFontSize=18, labelFontSize=15, symbolStrokeWidth=4, symbolSize=200),
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),
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strokeWidth=alt.condition(highlight, alt.value(5), alt.value(3)),
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opacity=alt.condition(highlight, alt.value(1), alt.value(0.7)),
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tooltip=["Cohort:N", "Week:Q", "Retention (%):Q"],
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# Build per-cohort line + point layers for graduated styling
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layers = []
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for cohort_label, info in cohorts.items():
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label = f"{cohort_label} (n={info['size']:,})"
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idx = info["order"]
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cohort_df = df[df["Cohort"] == label]
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line = (
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alt.Chart(cohort_df)
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.mark_line(strokeWidth=width_map[idx], opacity=opacity_map[idx])
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.encode(
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x=alt.X(
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"Week:Q",
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title="Weeks Since Signup",
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scale=alt.Scale(domain=[0, 12]),
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axis=alt.Axis(labelFontSize=18, titleFontSize=22, tickMinStep=1),
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),
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y=alt.Y(
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"Retention (%):Q",
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title="Retention (%)",
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scale=alt.Scale(domain=[0, 100]),
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axis=alt.Axis(labelFontSize=18, titleFontSize=22, format=".0f"),
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),
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color=alt.Color(
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"Cohort:N",
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scale=alt.Scale(domain=cohort_labels, range=colors),
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legend=alt.Legend(
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title="Cohort", titleFontSize=18, labelFontSize=15, symbolStrokeWidth=4, symbolSize=200
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),
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),
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strokeWidth=alt.condition(highlight, alt.value(6), alt.value(width_map[idx])),
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opacity=alt.condition(highlight, alt.value(1.0), alt.value(opacity_map[idx])),
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tooltip=["Cohort:N", "Week:Q", "Retention (%):Q"],
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)
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.add_params(highlight)
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)
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.add_params(highlight)
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)
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# Points on data values
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points = (
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alt.Chart(df)
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.mark_point(filled=True)
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.encode(
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x="Week:Q",
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y="Retention (%):Q",
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color=alt.Color("Cohort:N", scale=alt.Scale(domain=cohort_labels, range=colors), legend=None),
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size=alt.condition(highlight, alt.value(180), alt.value(80)),
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opacity=alt.condition(highlight, alt.value(1), alt.value(0.6)),
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tooltip=["Cohort:N", "Week:Q", "Retention (%):Q"],
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point = (
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alt.Chart(cohort_df)
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.mark_point(filled=True, size=60 + idx * 30)
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.encode(
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x="Week:Q",
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y="Retention (%):Q",
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color=alt.Color("Cohort:N", scale=alt.Scale(domain=cohort_labels, range=colors), legend=None),
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opacity=alt.condition(highlight, alt.value(1.0), alt.value(opacity_map[idx])),
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size=alt.condition(highlight, alt.value(200), alt.value(60 + idx * 30)),
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tooltip=["Cohort:N", "Week:Q", "Retention (%):Q"],
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)
8396
)
84-
)
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98+
layers.extend([line, point])
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86100
# Reference line at 20% retention threshold
87101
threshold_df = pd.DataFrame({"y": [20]})
88-
threshold = alt.Chart(threshold_df).mark_rule(strokeDash=[8, 6], strokeWidth=2, color="#888888").encode(y="y:Q")
102+
threshold = alt.Chart(threshold_df).mark_rule(strokeDash=[8, 6], strokeWidth=2, color="#666666").encode(y="y:Q")
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# Threshold label
91105
threshold_label = (
92106
alt.Chart(threshold_df)
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.mark_text(text="20% Target", align="left", dx=5, dy=-12, fontSize=16, color="#888888")
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.mark_text(text="20% Target", align="left", dx=5, dy=-12, fontSize=16, fontWeight="bold", color="#666666")
94108
.encode(x=alt.value(20), y="y:Q")
95109
)
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97111
# Combine layers
98112
chart = (
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(threshold + threshold_label + lines + points)
100-
.properties(width=1600, height=900, title=alt.Title("line-retention-cohort · altair · pyplots.ai", fontSize=28))
101-
.configure_axis(gridColor="#E0E0E0", gridOpacity=0.2)
113+
alt.layer(threshold, threshold_label, *layers)
114+
.properties(
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width=1600,
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height=900,
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title=alt.Title(
118+
"line-retention-cohort · altair · pyplots.ai",
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fontSize=28,
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fontWeight="bold",
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subtitle="Newer cohorts retain better — product improvements are working",
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subtitleFontSize=18,
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subtitleColor="#555555",
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),
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)
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.configure_axis(
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gridColor="#D0D0D0",
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gridOpacity=0.3,
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domainColor="#888888",
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tickColor="#888888",
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labelColor="#333333",
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titleColor="#222222",
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)
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.configure_view(strokeWidth=0)
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.configure(background="#FAFAFA")
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)
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# Save

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