Add example with hover path and search box

- point paths on hover
- search box to filter by country name

Relates to [#2980](#2980)

TODO:
- Investigate and potentially correct North Korea and South Korea data in vega_datasets' gapminder json, which appears to have swapped labels.

tests/examples_methods_syntax/scatter_point_paths_hover.py

@@ -0,0 +1,95 @@
+"""
+Scatter plot with point paths on hover with search box
+======================================================
+This example demonstrates an interactive visualization technique inspired by [this Vega example](https://vega.github.io/vega/examples/global-development/), 
+adapted for Altair's higher-level API. Key features:
+
+1. Visual Hint Paths: Displays trajectories of data items across time on hover, enabling intuitive understanding of how data evolves.
+2. Search Box: Allows filtering of data points by country name, extending the original concept with improved data exploration capabilities
+
+"""
+# category: interactive charts
+
+import altair as alt
+from vega_datasets import data
+
+# Data source
+source = data.gapminder.url
+
+# X-value slider
+x_slider = alt.binding_range(min=1955, max=2005, step=5, name='Year: ')
+x_select = alt.selection_point(name="x_select", fields=['year'], bind=x_slider, value=1980)
+
+# Hover selection
+hover = alt.selection_point(on='mouseover', fields=['country'], empty=False)
+
+# Search box for country name
+search_box = alt.param(
+    value='',
+    bind=alt.binding(input='search', placeholder="Country", name='Search ')
+)
+
+# Base chart
+base = alt.Chart(source).encode(
+    x=alt.X('fertility:Q', scale=alt.Scale(zero=False), title='Fertility'),
+    y=alt.Y('life_expect:Q', scale=alt.Scale(zero=False), title='Life Expectancy'),
+    color=alt.Color('region_name:N').legend(title='Region'),
+    detail='country:N'
+).transform_calculate(
+    region_name="{'0': 'South Asia', '1': 'Europe & Central Asia', '2': 'Sub-Saharan Africa', '3': 'America', '4': 'East Asia & Pacific', '5': 'Middle East & North Africa'}[datum.cluster]"
+)
+
+# Points that are always visible (filtered by slider and search)
+visible_points = base.mark_circle(size=100).encode(
+    opacity=alt.condition(x_select | search_box, alt.value(1), alt.value(0))
+).add_params(x_select).transform_filter(
+    x_select
+).transform_filter(
+    alt.expr.test(alt.expr.regexp(search_box, 'i'), alt.datum.country)
+).add_params(hover)
+
+# Line that appears on hover
+hover_line = base.mark_line(point=True).encode(
+    opacity=alt.condition(hover, alt.value(0.3), alt.value(0))
+)
+
+# Year labels
+year_labels = base.mark_text(align='left', dx=5, dy=-5).encode(
+    text='year:O'
+).transform_filter(hover)
+
+# Country labels
+country_labels = base.mark_text(align='left', dx=5, dy=-25, fontSize=24).encode(
+    text='country:N'
+).transform_filter(hover).transform_filter(x_select)
+
+background_year = alt.Chart(source).mark_text(
+    align='center',
+    baseline='middle',
+    fontSize=96,
+    opacity=0.2,
+    x='width',
+    y='height',
+    dx=-400,
+    dy=-300
+).encode(
+    text='year:O'
+).transform_filter(
+    x_select
+).transform_aggregate(
+    year='max(year)'  # This ensures we only get one label
+)
+
+# Combine all layers
+chart = alt.layer(
+    visible_points, year_labels, country_labels, hover_line, background_year
+).properties(
+    width=800,
+    height=600,
+    padding=50  # Padding required to ensure country labels fit
+).configure_axis(
+    labelFontSize=14,
+    titleFontSize=14
+).add_params(search_box)
+
+chart