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62 changes: 62 additions & 0 deletions altair/examples/cyperpunk_style_plot.py
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"""
Cyberpunk Style Plot
--------------------
Inspired by `this chart <https://towardsdatascience.com/cyberpunk-style-with-matplotlib-f47404c9d4c5>`_ by `@d_haitz <https://twitter.com/d_haitz>`_. This example shows how to layer line plots of varying size to create a neon glow effect.
"""
# category: case studies
import altair as alt
import pandas as pd

df = pd.DataFrame({'A': [1, 3, 9, 5, 2, 1, 1],
'B': [4, 5, 5, 7, 9, 8, 6]})

base = alt.Chart(
df.reset_index().melt(id_vars='index')
).encode(
x=alt.X('index:Q'),
y=alt.Y('value:Q'),
color=alt.Color('variable:N',
scale=alt.Scale(range=['#08F7FE', '#FE53BB']))
)

# draw lines and circles
chart = base.mark_circle(size=100, opacity=1)
chart += base.mark_line(size=2.5)

# make it glow
n_lines = 10
diff_linewidth = 1.25
alpha_value = 0.3 / n_lines

for n in range(n_lines):
line_width = 5 + (diff_linewidth * n)
chart += base.mark_line(opacity=alpha_value,
size=line_width)

# fill area underneath lines
chart += base.mark_area(opacity=0.1)

chart.configure_axis(
title=None,
ticks=False,
domain=False,
gridColor='#2A3459',
labelColor='#D3D3D3',
labelFontSize=14,
labelPadding=10,
labelSeparation=40
).configure_legend(
title=None,
labelColor='#D3D3D3',
labelFontSize=14,
orient='top-right',
symbolType='stroke',
symbolStrokeWidth=3,
symbolSize=600
).configure_view(
strokeWidth=0
).properties(
background='#212946',
width=600,
height=350
)
79 changes: 79 additions & 0 deletions altair/examples/faceted_bullet_chart.py
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"""
Faceted Bullet Chart
--------------------
This example shows how to facet and layer bar charts to create a bullet chart.
"""
# category: other charts
import altair as alt

source = {'values': [
{'title': 'Revenue', 'subtitle': 'US$, in thousands',
'ranges': [150, 225, 300], 'measures': [220, 270], 'markers': [250]
},
{'title': 'Profit', 'subtitle': '%',
'ranges': [20, 25, 30], 'measures': [21, 23], 'markers': [26]
},
{'title': 'Order Size', 'subtitle': 'US$, average',
'ranges': [350, 500, 600], 'measures': [100, 320], 'markers': [550]
},
{'title': 'New Customers', 'subtitle': 'count',
'ranges': [1400, 2000, 2500], 'measures': [1000, 1650], 'markers': [2100]
},
{'title': 'Satisfaction', 'subtitle': 'out of 5',
'ranges': [3.5, 4.25, 5], 'measures': [3.2, 4.7], 'markers': [4.4]
}
]}

base = alt.Chart(source)

chart = base.mark_bar(
).encode(
x=alt.X('ranges[2]:Q', scale=alt.Scale(nice=False)),
color=alt.value('#eee')
)

chart += base.mark_bar(
).encode(
x='ranges[1]:Q',
color=alt.value('#ddd')
)

chart += base.mark_bar(
).encode(
x='ranges[0]:Q',
color=alt.value('#ccc')
)

chart += base.mark_bar(
).encode(
x='measures[1]:Q',
color=alt.value('lightsteelblue'),
size=alt.value(10),
opacity=alt.value(1)
)

chart += base.mark_bar(
).encode(
x='measures[0]:Q',
color=alt.value('steelblue'),
size=alt.value(10)
)

chart += base.mark_tick(
).encode(
x='markers[0]:Q',
color=alt.value('black')
)

chart.facet(
row=alt.Row('title:N', title=None,
header=alt.Header(labelAngle=0, labelAlign='left', title=None))
).resolve_scale(
x='independent'
).configure_facet(
spacing=10
).configure_axis(
title=None
).configure_tick(
thickness=2
)
96 changes: 96 additions & 0 deletions altair/examples/weekly_weather_plot.py
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"""
Weekly Weather Plot
-------------------
Inspired by this `Vega-Lite example <https://vega.github.io/vega-lite/examples/bar_layered_weather.html>`_ by `@melissatdiamond <https://github.com/melissatdiamond>`_. This example shows how to layer bar charts to plot weekly weather data.
"""
# category: case studies
import altair as alt
from vega_datasets import data

source = data.weather()

base = alt.Chart(source).encode(
x=alt.X('id:O',
axis=alt.Axis(
domain=False,
ticks=False,
labels=False,
title=None,
titlePadding=25,
orient='top'
)
),
)

chart = base.mark_bar(
style='box'
).encode(
y=alt.Y('record.low:Q',
scale=alt.Scale(domain=[10, 70]),
axis=alt.Axis(title='Temperature (F)')
),
y2='record.high:Q',
size=alt.value(20),
color=alt.value('#ccc')
)

chart += base.mark_bar(
style='box'
).encode(
y='normal.low:Q',
y2='normal.high:Q',
size=alt.value(20),
color=alt.value('#999')
)

chart += base.mark_bar(
style='box'
).encode(
y='actual.low:Q',
y2='actual.high:Q',
size=alt.value(12),
color=alt.value('#000')
)

chart += base.mark_bar(
style='box'
).encode(
y='forecast.low.low:Q',
y2='forecast.low.high:Q',
size=alt.value(12),
color=alt.value('#000')
)

chart += base.mark_bar(
style='box'
).encode(
y='forecast.low.high:Q',
y2='forecast.high.high:Q',
size=alt.value(3),
color=alt.value('#000')
)

chart += base.mark_bar(
style='box'
).encode(
y='forecast.high.low:Q',
y2='forecast.high.high:Q',
size=alt.value(12),
color=alt.value('#000')
)

chart += base.mark_text(
align='center',
baseline='bottom',
).encode(
text='day:N',
y=alt.value(-5)
)

chart.properties(
title=['Weekly Weather', 'Observations and Predictions'],
width=250,
height=200
).configure_title(
frame='group'
)