Update to Vega-Lite 4.17.0

.github/workflows/build.yml

@@ -25,6 +25,7 @@ jobs:
         python -m pip install --upgrade pip
         pip install .[dev]
         pip install altair_saver
+        pip install git+git://github.com/altair-viz/altair_viewer.git
     - name: Test with pytest
       run: |
         pytest --doctest-modules altair

.github/workflows/docbuild.yml

@@ -21,8 +21,9 @@ jobs:
         pip install .[dev]
         pip install altair_saver
         pip install -r doc/requirements.txt
+        pip install git+git://github.com/altair-viz/altair_viewer.git
     - name: Run docbuild
       run: |
         cd doc && make ${{ matrix.build-type }}
 
-
+

.gitignore

@@ -69,4 +69,4 @@ Untitled*.ipynb
 *.DS_Store
 
 # VSCode
-.vscode
+.vscode

altair/examples/bar_chart_trellis_compact.py

@@ -0,0 +1,50 @@
+"""
+Compact Trellis Grid of Bar Charts
+==================================
+This example shows a simple grid of bar charts to compare performance data..
+"""
+# category: bar charts
+import altair as alt
+import pandas as pd
+
+source = pd.DataFrame(
+    [
+        {"a": "a1", "b": "b1", "c": "x", "p": "0.14"},
+        {"a": "a1", "b": "b1", "c": "y", "p": "0.60"},
+        {"a": "a1", "b": "b1", "c": "z", "p": "0.03"},
+        {"a": "a1", "b": "b2", "c": "x", "p": "0.80"},
+        {"a": "a1", "b": "b2", "c": "y", "p": "0.38"},
+        {"a": "a1", "b": "b2", "c": "z", "p": "0.55"},
+        {"a": "a1", "b": "b3", "c": "x", "p": "0.11"},
+        {"a": "a1", "b": "b3", "c": "y", "p": "0.58"},
+        {"a": "a1", "b": "b3", "c": "z", "p": "0.79"},
+        {"a": "a2", "b": "b1", "c": "x", "p": "0.83"},
+        {"a": "a2", "b": "b1", "c": "y", "p": "0.87"},
+        {"a": "a2", "b": "b1", "c": "z", "p": "0.67"},
+        {"a": "a2", "b": "b2", "c": "x", "p": "0.97"},
+        {"a": "a2", "b": "b2", "c": "y", "p": "0.84"},
+        {"a": "a2", "b": "b2", "c": "z", "p": "0.90"},
+        {"a": "a2", "b": "b3", "c": "x", "p": "0.74"},
+        {"a": "a2", "b": "b3", "c": "y", "p": "0.64"},
+        {"a": "a2", "b": "b3", "c": "z", "p": "0.19"},
+        {"a": "a3", "b": "b1", "c": "x", "p": "0.57"},
+        {"a": "a3", "b": "b1", "c": "y", "p": "0.35"},
+        {"a": "a3", "b": "b1", "c": "z", "p": "0.49"},
+        {"a": "a3", "b": "b2", "c": "x", "p": "0.91"},
+        {"a": "a3", "b": "b2", "c": "y", "p": "0.38"},
+        {"a": "a3", "b": "b2", "c": "z", "p": "0.91"},
+        {"a": "a3", "b": "b3", "c": "x", "p": "0.99"},
+        {"a": "a3", "b": "b3", "c": "y", "p": "0.80"},
+        {"a": "a3", "b": "b3", "c": "z", "p": "0.37"},
+    ]
+)
+
+alt.Chart(source, width=60, height=alt.Step(8)).mark_bar().encode(
+    y=alt.Y("c:N", axis=None),
+    x=alt.X("p:Q", title=None, axis=alt.Axis(format="%")),
+    color=alt.Color(
+        "c:N", title="settings", legend=alt.Legend(orient="bottom", titleOrient="left")
+    ),
+    row=alt.Row("a:N", title="Factor A", header=alt.Header(labelAngle=0)),
+    column=alt.Column("b:N", title="Factor B"),
+)

altair/examples/donut_chart.py

@@ -0,0 +1,18 @@
+"""
+Donut Chart
+-----------
+This example shows how to make a Donut Chart using ``mark_arc``.
+This is adapted from a corresponding Vega-Lite Example:
+`Donut Chart <https://vega.github.io/vega-lite/examples/arc_donut.html>`_.
+"""
+# category: circular plots
+
+import pandas as pd
+import altair as alt
+
+source = pd.DataFrame({"category": [1, 2, 3, 4, 5, 6], "value": [4, 6, 10, 3, 7, 8]})
+
+alt.Chart(source).mark_arc(innerRadius=50).encode(
+    theta=alt.Theta(field="value", type="quantitative"),
+    color=alt.Color(field="category", type="nominal"),
+)

altair/examples/line_chart_with_color_datum.py

@@ -0,0 +1,21 @@
+"""
+Line Chart with datum for color
+-------------------------------
+An example of using ``datum`` and ``repeat`` to color a multi-series line chart.
+This is adapted from this corresponding Vega-Lite Example:
+`Repeat and Layer to Show Different Movie Measures <https://vega.github.io/vega-lite/examples/repeat_layer.html>`_.
+"""
+# category: line charts
+
+import altair as alt
+from vega_datasets import data
+
+source = data.movies()
+
+alt.Chart(source).mark_line().encode(
+    x=alt.X("IMDB_Rating", bin=True),
+    y=alt.Y(
+        alt.repeat("layer"), aggregate="mean", title="Mean of US and Worldwide Gross"
+    ),
+    color=alt.datum(alt.repeat("layer")),
+).repeat(layer=["US_Gross", "Worldwide_Gross"])

altair/examples/line_chart_with_datum.py

@@ -0,0 +1,33 @@
+"""
+Line Chart with datum
+---------------------------------
+An example of using ``datum`` to highlight certain values, including a ``DateTime`` value.
+This is adapted from two corresponding Vega-Lite Examples:
+`Highlight a Specific Value <https://vega.github.io/vega-lite/docs/datum.html#highlight-a-specific-data-value>`_.
+"""
+# category: line charts
+
+import altair as alt
+from vega_datasets import data
+
+source = data.stocks()
+no_source = alt.Data(values=[{}])
+
+lines = (
+    alt.Chart(source)
+    .mark_line()
+    .encode(x=alt.X("date"), y=alt.Y("price"), color="symbol")
+)
+
+xrule = (
+    alt.Chart(no_source)
+    .mark_rule(color="cyan", strokeWidth=2)
+    .encode(x=alt.datum(alt.DateTime(year=2006, month="November")))
+)
+
+yrule = (
+    alt.Chart(no_source).mark_rule(strokeDash=[12, 6], size=2).encode(y=alt.datum(350))
+)
+
+
+lines + yrule + xrule

altair/examples/pacman_chart.py

@@ -0,0 +1,19 @@
+"""
+Pacman Chart
+------------
+Chart made using ``mark_arc`` and constant values.
+This could also be made using 
+``alt.Chart(source).mark_arc(color = "gold", theta = (5/8)*np.pi, theta2 = (19/8)*np.pi,radius=100)``.
+"""
+# category: circular plots
+
+import numpy as np
+import altair as alt
+
+no_source = alt.Data(values=[{}])
+
+alt.Chart(no_source).mark_arc(color="gold").encode(
+    theta=alt.datum((5 / 8) * np.pi, scale=None),
+    theta2=alt.datum((19 / 8) * np.pi),
+    radius=alt.datum(100, scale=None),
+)

altair/examples/pie_chart.py

@@ -0,0 +1,18 @@
+"""
+Pie Chart
+---------
+This example shows how to make a Pie Chart using ``mark_arc``.
+This is adapted from a corresponding Vega-Lite Example:
+`Pie Chart <https://vega.github.io/vega-lite/examples/arc_pie.html>`_.
+"""
+# category: circular plots
+
+import pandas as pd
+import altair as alt
+
+source = pd.DataFrame({"category": [1, 2, 3, 4, 5, 6], "value": [4, 6, 10, 3, 7, 8]})
+
+alt.Chart(source).mark_arc().encode(
+    theta=alt.Theta(field="value", type="quantitative"),
+    color=alt.Color(field="category", type="nominal"),
+)

altair/examples/pie_chart_with_labels.py

@@ -0,0 +1,24 @@
+"""
+Pie Chart with Labels
+---------------------
+This example shows how to layer text over arc marks (``mark_arc``) to label pie charts.
+This is adapted from a corresponding Vega-Lite Example:
+`Pie Chart with Labels <https://vega.github.io/vega-lite/examples/layer_arc_label.html>`_.
+"""
+# category: circular plots
+
+import pandas as pd
+import altair as alt
+
+source = pd.DataFrame(
+    {"category": ["a", "b", "c", "d", "e", "f"], "value": [4, 6, 10, 3, 7, 8]}
+)
+
+base = alt.Chart(source).encode(
+    theta=alt.Theta("value:Q", stack=True), color=alt.Color("category:N", legend=None)
+)
+
+pie = base.mark_arc(outerRadius=120)
+text = base.mark_text(radius=140, size=20).encode(text="category:N")
+
+pie + text

altair/examples/radial_chart.py

@@ -0,0 +1,25 @@
+"""
+Radial Chart
+------------
+This radial plot uses both angular and radial extent to convey multiple dimensions of data.
+This is adapted from a corresponding Vega-Lite Example:
+`Radial Plot <https://vega.github.io/vega-lite/examples/arc_radial.html>`_.
+"""
+# category: circular plots
+
+import pandas as pd
+import altair as alt
+
+source = pd.DataFrame({"values": [12, 23, 47, 6, 52, 19]})
+
+base = alt.Chart(source).encode(
+    theta=alt.Theta("values:Q", stack=True),
+    radius=alt.Radius("values", scale=alt.Scale(type="sqrt", zero=True, rangeMin=20)),
+    color="values:N",
+)
+
+c1 = base.mark_arc(innerRadius=20, stroke="#fff")
+
+c2 = base.mark_text(radiusOffset=10).encode(text="values:Q")
+
+c1 + c2

altair/examples/wind_vector_map.py

@@ -0,0 +1,24 @@
+"""
+Wind Vector Map
+---------------
+An example showing a vector array map showing wind speed and direction using ``wedge``
+as shape for ``mark_point`` and ``angle`` encoding for the wind direction.
+This is adapted from this corresponding Vega-Lite Example:
+`Wind Vector Map <https://vega.github.io/vega-lite/examples/point_angle_windvector.html>`_.
+"""
+# category: scatter plots
+
+import altair as alt
+from vega_datasets import data
+
+source = data.windvectors()
+
+alt.Chart(source).mark_point(shape="wedge", filled=True).encode(
+    latitude="latitude",
+    longitude="longitude",
+    color=alt.Color(
+        "dir", scale=alt.Scale(domain=[0, 360], scheme="rainbow"), legend=None
+    ),
+    angle=alt.Angle("dir", scale=alt.Scale(domain=[0, 360], range=[180, 540])),
+    size=alt.Size("speed", scale=alt.Scale(rangeMax=500)),
+).project("equalEarth")

altair/expr/core.py

@@ -15,6 +15,10 @@ def __getattr__(self, attr):
     def __getitem__(self, attr):
         return GetItemExpression("datum", attr)
 
+    def __call__(self, datum, **kwargs):
+        """Specify a datum for use in an encoding"""
+        return dict(datum=datum, **kwargs)
+
 
 datum = DatumType()
 

altair/sphinxext/altairgallery.py

@@ -265,6 +265,7 @@ def main(app):
             "Bar Charts": [],
             "Line Charts": [],
             "Area Charts": [],
+            "Circular Plots": [],
             "Scatter Plots": [],
             "Histograms": [],
             "Maps": [],