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[Doc] Add scatter plot with shaded area example
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ChiaLingWeng committed Nov 8, 2023
1 parent 18ce6fb commit 792d1b4
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48 changes: 48 additions & 0 deletions tests/examples_arguments_syntax/scatter_with_shaded_area.py
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"""
Scatter Plot with Shaded Area
-----------------------------
This example shows a scatter plot with shaded area,
constructed using :ref:`area mark <user-guide-area-marks>` and :ref:`rect mark <user-guide-rect-marks>`.
"""
# category: scatter plots

import altair as alt
import pandas as pd
import numpy as np

data = pd.DataFrame({
"x": np.random.uniform(-4, 5, size=50),
"y": np.random.uniform(2, 5, size=50),
})

rect_data = pd.DataFrame({
"x1": [-2],
"x2": [-1]
})

# define this interval between y = -x and y = -x
df = pd.DataFrame({
"x": range(7),
"ymin": range(7),
"ymax": range(1,8)
})

points = alt.Chart(data).mark_point().encode(
x="x",
y="y"
)

interval = alt.Chart(df).mark_area(opacity=0.3).encode(
x="x:Q",
y="ymin:Q",
y2="ymax:Q"
)


rect = alt.Chart(rect_data).mark_rect(opacity=0.3).encode(
x="x1",
x2="x2",
color=alt.ColorValue("#FF0000")
)

points + interval + rect
48 changes: 48 additions & 0 deletions tests/examples_methods_syntax/scatter_with_shaded_area.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,48 @@
"""
Scatter Plot with Shaded Area
-----------------------------
This example shows a scatter plot with shaded area,
constructed using :ref:`area mark <user-guide-area-marks>` and :ref:`rect mark <user-guide-rect-marks>`.
"""
# category: scatter plots

import altair as alt
import pandas as pd
import numpy as np

data = pd.DataFrame({
"x": np.random.uniform(-4, 5, size=50),
"y": np.random.uniform(2, 5, size=50),
})

rect_data = pd.DataFrame({
"x1": [-2],
"x2": [-1]
})

# define this interval between y = -x and y = -x
df = pd.DataFrame({
"x": range(7),
"ymin": range(7),
"ymax": range(1,8)
})

points = alt.Chart(data).mark_point().encode(
x="x",
y="y"
)

interval = alt.Chart(df).mark_area(opacity=0.3).encode(
x="x:Q",
y="ymin:Q",
y2="ymax:Q"
)


rect = alt.Chart(rect_data).mark_rect(opacity=0.3).encode(
x="x1",
x2="x2",
color=alt.ColorValue("#FF0000")
)

points + interval + rect

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