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61 lines
1.6 KiB
Python
61 lines
1.6 KiB
Python
"""
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Seattle Weather Interactive
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===========================
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This chart provides an interactive exploration of Seattle weather over the
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course of the year. It includes a one-axis brush selection to easily
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see the distribution of weather types in a particular date range.
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"""
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# category: case studies
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import altair as alt
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from vega_datasets import data
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source = data.seattle_weather()
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scale = alt.Scale(domain=['sun', 'fog', 'drizzle', 'rain', 'snow'],
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range=['#e7ba52', '#a7a7a7', '#aec7e8', '#1f77b4', '#9467bd'])
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color = alt.Color('weather:N', scale=scale)
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# We create two selections:
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# - a brush that is active on the top panel
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# - a multi-click that is active on the bottom panel
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brush = alt.selection_interval(encodings=['x'])
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click = alt.selection_multi(encodings=['color'])
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# Top panel is scatter plot of temperature vs time
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points = alt.Chart().mark_point().encode(
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alt.X('monthdate(date):T', title='Date'),
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alt.Y('temp_max:Q',
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title='Maximum Daily Temperature (C)',
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scale=alt.Scale(domain=[-5, 40])
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),
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color=alt.condition(brush, color, alt.value('lightgray')),
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size=alt.Size('precipitation:Q', scale=alt.Scale(range=[5, 200]))
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).properties(
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width=550,
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height=300
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).add_selection(
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brush
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).transform_filter(
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click
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)
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# Bottom panel is a bar chart of weather type
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bars = alt.Chart().mark_bar().encode(
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x='count()',
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y='weather:N',
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color=alt.condition(click, color, alt.value('lightgray')),
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).transform_filter(
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brush
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).properties(
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width=550,
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).add_selection(
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click
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)
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alt.vconcat(
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points,
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bars,
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data=source,
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title="Seattle Weather: 2012-2015"
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)
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