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feat(plotly): implement map-tile-background (#7755)
## Implementation: `map-tile-background` - python/plotly Implements the **python/plotly** version of `map-tile-background`. **File:** `plots/map-tile-background/implementations/python/plotly.py` **Parent Issue:** #3756 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/26520049241)* --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com>
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‎plots/map-tile-background/implementations/python/plotly.py‎

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""" pyplots.ai
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""" anyplot.ai
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map-tile-background: Map with Tile Background
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Library: plotly 6.5.2 | Python 3.13.11
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Quality: 91/100 | Created: 2026-01-20
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Library: plotly 6.7.0 | Python 3.13.13
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Quality: 87/100 | Updated: 2026-05-27
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"""
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import os
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import sys
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# Remove this script's directory from sys.path so "plotly.py" doesn't shadow
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# the installed plotly package when Python prepends the script dir.
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_script_dir = os.path.dirname(os.path.abspath(__file__))
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sys.path = [p for p in sys.path if os.path.abspath(p) != _script_dir]
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import numpy as np
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import plotly.graph_objects as go
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# Data - European City Landmarks
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THEME = os.getenv("ANYPLOT_THEME", "light")
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# Theme-adaptive chrome
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PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
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ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
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INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
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INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
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# Anyplot sequential colorscale: brand green → blue (single-polarity continuous)
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imprint_seq = [[0.0, "#009E73"], [1.0, "#4467A3"]]
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# Theme-adaptive map tile style
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map_style = "open-street-map" if THEME == "light" else "carto-darkmatter"
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# Data — European City Landmarks with annual visitor counts
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np.random.seed(42)
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# Major European city landmarks with simulated visitor counts
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landmarks = {
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"name": [
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"Eiffel Tower",
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"Colosseum",
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"Sagrada Familia",
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"Big Ben",
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"Brandenburg Gate",
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"Anne Frank House",
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"Acropolis",
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"Charles Bridge",
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"St. Stephen's Basilica",
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"Royal Palace",
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"Manneken Pis",
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"Tivoli Gardens",
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"Schonbrunn Palace",
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"Old Town Square",
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"Rialto Bridge",
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],
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"lat": [
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48.8584,
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41.8902,
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41.4036,
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51.5007,
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52.5163,
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52.3752,
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37.9715,
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50.0865,
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47.5008,
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59.3268,
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50.8450,
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55.6736,
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48.1845,
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50.0870,
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45.4380,
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],
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"lon": [
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2.2945,
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12.4922,
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2.1744,
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-0.1246,
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13.3777,
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4.8840,
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23.7267,
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14.4114,
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19.0538,
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18.0717,
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4.3499,
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12.5681,
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16.3119,
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14.4208,
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12.3358,
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],
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"visitors": [
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7000000,
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7400000,
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4500000,
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2000000,
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3000000,
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1300000,
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3000000,
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5000000,
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1000000,
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1500000,
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500000,
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4000000,
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4000000,
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6000000,
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5000000,
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],
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}
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names = [
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"Eiffel Tower",
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"Colosseum",
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"Sagrada Familia",
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"Big Ben",
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"Brandenburg Gate",
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"Anne Frank House",
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"Acropolis",
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"Charles Bridge",
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"St. Stephen's Basilica",
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"Royal Palace",
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"Manneken Pis",
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"Tivoli Gardens",
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"Schönbrunn Palace",
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"Dubrovnik Old Walls",
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"Rialto Bridge",
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]
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lats = [
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48.8584, # Eiffel Tower
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41.8902, # Colosseum
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41.4036, # Sagrada Familia
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51.5007, # Big Ben
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52.5163, # Brandenburg Gate
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52.3752, # Anne Frank House
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37.9715, # Acropolis
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50.0865, # Charles Bridge
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47.5008, # St. Stephen's Basilica
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59.3268, # Royal Palace
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50.8450, # Manneken Pis
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55.6736, # Tivoli Gardens
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48.1845, # Schönbrunn Palace
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42.6411, # Dubrovnik Old Walls
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45.4380, # Rialto Bridge
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]
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lons = [
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2.2945, # Eiffel Tower
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12.4922, # Colosseum
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2.1744, # Sagrada Familia
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-0.1246, # Big Ben
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13.3777, # Brandenburg Gate
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4.8840, # Anne Frank House
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23.7267, # Acropolis
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14.4114, # Charles Bridge
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19.0538, # St. Stephen's Basilica
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18.0717, # Royal Palace
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4.3499, # Manneken Pis
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12.5681, # Tivoli Gardens
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16.3119, # Schönbrunn Palace
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18.1085, # Dubrovnik Old Walls
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12.3358, # Rialto Bridge
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]
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visitors = np.array(
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[
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7_000_000, # Eiffel Tower
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7_400_000, # Colosseum
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4_500_000, # Sagrada Familia
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2_000_000, # Big Ben
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3_000_000, # Brandenburg Gate
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1_300_000, # Anne Frank House
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3_000_000, # Acropolis
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5_000_000, # Charles Bridge
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1_000_000, # St. Stephen's Basilica
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1_500_000, # Royal Palace
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500_000, # Manneken Pis
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4_000_000, # Tivoli Gardens
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4_000_000, # Schönbrunn Palace
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1_200_000, # Dubrovnik Old Walls
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5_000_000, # Rialto Bridge
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]
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)
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# Convert visitors to marker sizes (scaled for visibility)
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visitors = np.array(landmarks["visitors"])
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# Scale visitor counts to marker diameters (15–50 px range)
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sizes = 15 + (visitors - visitors.min()) / (visitors.max() - visitors.min()) * 35
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vmin, vmax = int(visitors.min()), int(visitors.max())
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# Split into two groups to alternate textposition for the crowded NW Europe cluster:
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# "bottom center" for Big Ben, St. Stephen's, Schönbrunn, Manneken Pis, Colosseum, Rialto
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bottom_idx = {3, 8, 12, 10, 1, 14}
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top_idx = set(range(len(names))) - bottom_idx
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def _select(seq, indices):
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return [seq[i] for i in sorted(indices)]
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# Create the map figure with tile background
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fig = go.Figure()
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# Add scattermap trace for data points on tile background (new API replacing scattermapbox)
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# Main trace (top center labels) — carries colorbar
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fig.add_trace(
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go.Scattermap(
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lat=landmarks["lat"],
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lon=landmarks["lon"],
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lat=_select(lats, top_idx),
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lon=_select(lons, top_idx),
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mode="markers+text",
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marker=dict(
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size=sizes,
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color=visitors,
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colorscale=[[0, "#306998"], [0.5, "#4a8bc2"], [1, "#FFD43B"]],
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colorbar=dict(
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title=dict(text="Annual Visitors", font=dict(size=18)), tickfont=dict(size=14), thickness=20, len=0.7
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),
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opacity=0.85,
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),
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text=landmarks["name"],
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marker={
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"size": _select(list(sizes), top_idx),
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"color": _select(list(visitors), top_idx),
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"colorscale": imprint_seq,
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"cmin": vmin,
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"cmax": vmax,
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"colorbar": {
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"title": {"text": "Annual Visitors", "font": {"size": 12, "color": INK}},
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"tickfont": {"size": 10, "color": INK_SOFT},
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"bgcolor": ELEVATED_BG,
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"bordercolor": INK_SOFT,
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"borderwidth": 1,
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"thickness": 18,
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"len": 0.65,
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"tickformat": ",.0f",
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},
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"opacity": 0.85,
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},
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text=_select(names, top_idx),
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textposition="top center",
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textfont=dict(size=12, color="black"),
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hovertemplate="<b>%{text}</b><br>"
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+ "Lat: %{lat:.4f}<br>"
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+ "Lon: %{lon:.4f}<br>"
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+ "Visitors: %{marker.color:,.0f}<extra></extra>",
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textfont={"size": 11, "color": INK},
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hovertemplate=("<b>%{text}</b><br>Visitors: %{marker.color:,.0f}<extra></extra>"),
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)
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)
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# Secondary trace (bottom center labels) — no colorbar, same scale
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fig.add_trace(
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go.Scattermap(
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lat=_select(lats, bottom_idx),
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lon=_select(lons, bottom_idx),
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mode="markers+text",
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marker={
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"size": _select(list(sizes), bottom_idx),
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"color": _select(list(visitors), bottom_idx),
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"colorscale": imprint_seq,
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"cmin": vmin,
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"cmax": vmax,
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"showscale": False,
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"opacity": 0.85,
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},
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text=_select(names, bottom_idx),
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textposition="bottom center",
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textfont={"size": 11, "color": INK},
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hovertemplate=("<b>%{text}</b><br>Visitors: %{marker.color:,.0f}<extra></extra>"),
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)
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)
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# Update layout with OpenStreetMap tile background (new 'map' API replacing 'mapbox')
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fig.update_layout(
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title=dict(
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text="European Landmarks Visitor Data<br>"
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"<span style='font-size:20px'>map-tile-background \u00b7 plotly \u00b7 pyplots.ai</span>",
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font=dict(size=28),
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x=0.5,
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xanchor="center",
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),
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map=dict(style="open-street-map", center=dict(lat=48.5, lon=10.0), zoom=3.5),
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margin=dict(l=20, r=20, t=100, b=20),
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autosize=False,
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paper_bgcolor=PAGE_BG,
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font={"color": INK},
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title={
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"text": (
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"European Landmarks by Visitor Count<br>"
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"<span style='font-size:12px'>"
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"map-tile-background · python · plotly · anyplot.ai"
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"</span>"
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),
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"font": {"size": 16, "color": INK},
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"x": 0.5,
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"xanchor": "center",
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},
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map={"style": map_style, "center": {"lat": 48.5, "lon": 10.0}, "zoom": 3.5},
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margin={"l": 20, "r": 20, "t": 80, "b": 20},
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showlegend=False,
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annotations=[
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{
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"text": "<b>★ Top attraction</b><br>Colosseum · 7.4M visitors/yr",
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"xref": "paper",
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"yref": "paper",
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"x": 0.68,
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"y": 0.22,
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"showarrow": False,
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"font": {"size": 11, "color": "#009E73"},
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"bgcolor": ELEVATED_BG,
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"bordercolor": "#009E73",
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"borderwidth": 1,
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"borderpad": 5,
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"align": "left",
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}
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],
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)
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# Save as PNG (4800x2700 at scale 3)
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fig.write_image("plot.png", width=1600, height=900, scale=3)
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# Save interactive HTML version
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fig.write_html("plot.html", include_plotlyjs="cdn")
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fig.write_image(f"plot-{THEME}.png", width=800, height=450, scale=4)
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fig.write_html(f"plot-{THEME}.html", include_plotlyjs="cdn")

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