Add method based attribute setting to encoding classes for Altair 5

altair/examples/airport_connections.py

@@ -1,8 +1,8 @@
 """
 Connections Among U.S. Airports Interactive
 -------------------------------------------
-This example shows all the connections between major U.S. airports. Lookup transformations 
-are used to find the coordinates of each airport and connecting airports. Connections 
+This example shows all the connections between major U.S. airports. Lookup transformations
+are used to find the coordinates of each airport and connecting airports. Connections
 are displayed on mouseover via a single selection.
 """
 # category: case studies
@@ -26,10 +26,10 @@
 )
 
 background = alt.Chart(states).mark_geoshape(
-    fill="lightgray", 
+    fill="lightgray",
     stroke="white"
 ).properties(
-    width=750, 
+    width=750,
     height=500
 ).project("albersUsa")
 
@@ -39,11 +39,11 @@
     latitude2="lat2:Q",
     longitude2="lon2:Q"
 ).transform_lookup(
-    lookup="origin", 
+    lookup="origin",
     from_=lookup_data
 ).transform_lookup(
-    lookup="destination", 
-    from_=lookup_data, 
+    lookup="destination",
+    from_=lookup_data,
     as_=["state", "lat2", "lon2"]
 ).transform_filter(
     select_city
@@ -52,14 +52,14 @@
 points = alt.Chart(flights_airport).mark_circle().encode(
     latitude="latitude:Q",
     longitude="longitude:Q",
-    size=alt.Size("routes:Q", scale=alt.Scale(range=[0, 1000]), legend=None),
-    order=alt.Order("routes:Q", sort="descending"),
+    size=alt.Size("routes:Q").legend(None).scale(range=[0, 1000]),
+    order=alt.Order("routes:Q").sort("descending"),
     tooltip=["origin:N", "routes:Q"]
 ).transform_aggregate(
-    routes="count()", 
+    routes="count()",
     groupby=["origin"]
 ).transform_lookup(
-    lookup="origin", 
+    lookup="origin",
     from_=lookup_data
 ).transform_filter(
     (alt.datum.state != "PR") & (alt.datum.state != "VI")

altair/examples/annual_weather_heatmap.py

@@ -9,11 +9,16 @@
 source = data.seattle_weather()
 
 alt.Chart(source, title="Daily Max Temperatures (C) in Seattle, WA").mark_rect().encode(
-    x=alt.X("date(date):O", title="Day", axis=alt.Axis(format="%e", labelAngle=0)),
-    y=alt.Y("month(date):O", title="Month"),
-    color=alt.Color("max(temp_max)", legend=alt.Legend(title=None)),
+    alt.X("date(date):O").title("Day").axis(format="%e", labelAngle=0),
+    alt.Y("month(date):O").title("Month"),
+    alt.Color("max(temp_max)").title(None),
     tooltip=[
         alt.Tooltip("monthdate(date)", title="Date"),
         alt.Tooltip("max(temp_max)", title="Max Temp"),
     ],
-).configure_view(step=13, strokeWidth=0).configure_axis(domain=False)
+).configure_view(
+    step=13,
+    strokeWidth=0
+).configure_axis(
+    domain=False
+)

altair/examples/anscombe_plot.py

@@ -11,8 +11,8 @@
 source = data.anscombe()
 
 alt.Chart(source).mark_circle().encode(
-    alt.X('X', scale=alt.Scale(zero=False)),
-    alt.Y('Y', scale=alt.Scale(zero=False)),
+    alt.X('X').scale(zero=False),
+    alt.Y('Y').scale(zero=False),
     alt.Facet('Series', columns=2),
 ).properties(
     width=180,

altair/examples/bar_chart_trellis_compact.py

@@ -40,11 +40,9 @@
 )
 
 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"),
+    alt.Y("c:N").axis(None),
+    alt.X("p:Q").title(None).axis(format="%"),
+    alt.Color("c:N").title("settings").legend(orient="bottom", titleOrient="left"),
+    alt.Row("a:N").title("Factor A").header(labelAngle=0),
+    alt.Column("b:N").title("Factor B"),
 )

altair/examples/beckers_barley_trellis_plot.py

@@ -10,24 +10,19 @@
 source = data.barley()
 
 alt.Chart(source, title="The Morris Mistake").mark_point().encode(
-    alt.X(
-        'yield:Q',
-        title="Barley Yield (bushels/acre)",
-        scale=alt.Scale(zero=False),
-        axis=alt.Axis(grid=False)
-    ),
-    alt.Y(
-        'variety:N',
-        title="",
-        sort='-x',
-        axis=alt.Axis(grid=True)
-    ),
-    color=alt.Color('year:N', legend=alt.Legend(title="Year")),
-    row=alt.Row(
-        'site:N',
-        title="",
-        sort=alt.EncodingSortField(field='yield', op='sum', order='descending'),
-    )
+    alt.X('yield:Q')
+        .title("Barley Yield (bushels/acre)")
+        .scale(zero=False)
+        .axis(grid=False),
+    alt.Y('variety:N')
+        .title("")
+        .sort('-x')
+        .axis(grid=True),
+    alt.Color('year:N')
+        .legend(title="Year"),
+    alt.Row('site:N')
+        .title("")
+        .sort(alt.EncodingSortField(field='yield', op='sum', order='descending'))
 ).properties(
     height=alt.Step(20)
 ).configure_view(stroke="transparent")

altair/examples/beckers_barley_wrapped_facet.py

@@ -12,7 +12,7 @@
 source = data.barley.url
 
 alt.Chart(source).mark_point().encode(
-    alt.X('median(yield):Q', scale=alt.Scale(zero=False)),
+    alt.X('median(yield):Q').scale(zero=False),
     y='variety:O',
     color='year:N',
     facet=alt.Facet('site:O', columns=2),

altair/examples/bump_chart.py

@@ -14,8 +14,8 @@
 stocks = data.stocks()
 source = stocks.groupby([pd.Grouper(key="date", freq="6M"),"symbol"]).mean().reset_index()
 
-alt.Chart(source).mark_line(point = True).encode(
-    x = alt.X("date:O", timeUnit="yearmonth", title="date"),
+alt.Chart(source).mark_line(point=True).encode(
+    x=alt.X("date:O").timeUnit("yearmonth").title("date"),
     y="rank:O",
     color=alt.Color("symbol:N")
 ).transform_window(
@@ -26,4 +26,4 @@
     title="Bump Chart for Stock Prices",
     width=600,
     height=150,
-)
+)

altair/examples/candlestick_chart.py

@@ -12,27 +12,23 @@
 
 source = data.ohlc()
 
-open_close_color = alt.condition("datum.open <= datum.close",
-                                 alt.value("#06982d"),
-                                 alt.value("#ae1325"))
+open_close_color = alt.condition(
+    "datum.open <= datum.close",
+    alt.value("#06982d"),
+    alt.value("#ae1325")
+)
 
 base = alt.Chart(source).encode(
-    alt.X('date:T',
-          axis=alt.Axis(
-              format='%m/%d', 
-              labelAngle=-45, 
-              title='Date in 2009'
-          )
-    ),
+    alt.X('date:T')
+        .axis(format='%m/%d', labelAngle=-45)
+        .title('Date in 2009'),
     color=open_close_color
 )
 
 rule = base.mark_rule().encode(
-    alt.Y(
-        'low:Q',
-        title='Price',
-        scale=alt.Scale(zero=False),
-    ),
+    alt.Y('low:Q')
+        .title('Price')
+        .scale(zero=False),
     alt.Y2('high:Q')
 )
 
@@ -41,4 +37,4 @@
     alt.Y2('close:Q')
 )
 
-rule + bar
+rule + bar

altair/examples/co2_concentration.py

@@ -27,25 +27,24 @@
     groupby=['decade'],
     frame=[None, None]
 ).transform_calculate(
-  end="datum.first_date === datum.scaled_date ? 'first' : datum.last_date === datum.scaled_date ? 'last' : null"
+  end=(
+      "datum.first_date === datum.scaled_date ? 'first'"
+      ": datum.last_date === datum.scaled_date ? 'last'"
+      ": null"
+  )
 ).encode(
-    x=alt.X(
-        "scaled_date:Q",
-        axis=alt.Axis(title="Year into Decade", tickCount=11)
-    ),
-    y=alt.Y(
-        "CO2:Q",
-        title="CO2 concentration in ppm",
-        scale=alt.Scale(zero=False)
-    )
+    alt.X("scaled_date:Q")
+        .title("Year into Decade")
+        .axis(tickCount=11),
+    alt.Y("CO2:Q")
+        .title("CO2 concentration in ppm")
+        .scale(zero=False)
 )
 
 line = base.mark_line().encode(
-    color=alt.Color(
-        "decade:O",
-        scale=alt.Scale(scheme="magma"),
-        legend=None
-    )
+    alt.Color("decade:O")
+        .scale(scheme="magma")
+        .legend(None)
 )
 
 text = base.encode(text="year:N")

altair/examples/comet_chart.py

@@ -11,22 +11,34 @@
 import altair as alt
 import vega_datasets
 
-(
-    alt.Chart(vega_datasets.data.barley.url)
-    .transform_pivot("year", value="yield", groupby=["variety", "site"])
-    .transform_fold(["1931", "1932"], as_=["year", "yield"])
-    .transform_calculate(calculate="datum['1932'] - datum['1931']", as_="delta")
-    .mark_trail()
-    .encode(
-        x=alt.X('year:O', title=None), 
-        y=alt.Y('variety:N', title='Variety'),
-        size=alt.Size('yield:Q', scale=alt.Scale(range=[0, 12]), legend=alt.Legend(values=[20, 60], title='Barley Yield (bushels/acre)')),
-        color=alt.Color('delta:Q', scale=alt.Scale(domainMid=0), legend=alt.Legend(title='Yield Delta (%)')),
-        tooltip=alt.Tooltip(['year:O', 'yield:Q']),
-        column=alt.Column('site:N', title='Site')
-
-    )
-    .configure_view(stroke=None)
-    .configure_legend(orient='bottom', direction='horizontal')
-    .properties(title='Barley Yield comparison between 1932 and 1931')
+alt.Chart(
+    vega_datasets.data.barley.url,
+    title='Barley Yield comparison between 1932 and 1931'
+).mark_trail().encode(
+    alt.X('year:O').title(None),
+    alt.Y('variety:N').title('Variety'),
+    alt.Size('yield:Q')
+        .scale(range=[0, 12])
+        .legend(values=[20, 60])
+        .title('Barley Yield (bushels/acre)'),
+    alt.Color('delta:Q')
+        .scale(domainMid=0)
+        .title('Yield Delta (%)'),
+    alt.Tooltip(['year:O', 'yield:Q']),
+    alt.Column('site:N').title('Site')
+).transform_pivot(
+    "year",
+    value="yield",
+    groupby=["variety", "site"]
+).transform_fold(
+    ["1931", "1932"],
+    as_=["year", "yield"]
+).transform_calculate(
+    calculate="datum['1932'] - datum['1931']",
+    as_="delta"
+).configure_legend(
+    orient='bottom',
+    direction='horizontal'
+).configure_view(
+    stroke=None
 )

altair/examples/connected_scatterplot.py

@@ -12,7 +12,7 @@
 source = data.driving()
 
 alt.Chart(source).mark_line(point=True).encode(
-    alt.X('miles', scale=alt.Scale(zero=False)),
-    alt.Y('gas', scale=alt.Scale(zero=False)),
+    alt.X('miles').scale(zero=False),
+    alt.Y('gas').scale(zero=False),
     order='year'
 )

altair/examples/density_stack.py

@@ -30,6 +30,6 @@
     steps=200
 ).mark_area().encode(
     alt.X('value:Q'), 
-    alt.Y('density:Q', stack='zero'),
+    alt.Y('density:Q').stack('zero'),
     alt.Color('Measurement_type:N')
 ).properties(width=400, height=100)

altair/examples/diverging_stacked_bar_chart.py

@@ -358,10 +358,6 @@
 alt.Chart(source).mark_bar().encode(
     x='percentage_start:Q',
     x2='percentage_end:Q',
-    y=alt.Y('question:N', axis=y_axis),
-    color=alt.Color(
-        'type:N',
-        legend=alt.Legend( title='Response'),
-        scale=color_scale,
-    )
+    y=alt.Y('question:N').axis(y_axis),
+    color=alt.Color('type:N').title('Response').scale(color_scale),
 )

altair/examples/donut_chart.py

@@ -10,9 +10,12 @@
 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]})
+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"),
+    theta="value",
+    color="category:N",
 )

altair/examples/dot_dash_plot.py

@@ -16,23 +16,23 @@
 
 # Configure the points
 points = base.mark_point().encode(
-    x=alt.X('Miles_per_Gallon', title=''),
-    y=alt.Y('Horsepower', title=''),
+    alt.X('Miles_per_Gallon').title(''),
+    alt.Y('Horsepower').title(''),
     color=alt.condition(brush, 'Origin', alt.value('grey'))
 )
 
 # Configure the ticks
 tick_axis = alt.Axis(labels=False, domain=False, ticks=False)
 
 x_ticks = base.mark_tick().encode(
-    alt.X('Miles_per_Gallon', axis=tick_axis),
-    alt.Y('Origin', title='', axis=tick_axis),
+    alt.X('Miles_per_Gallon').axis(tick_axis),
+    alt.Y('Origin').title('').axis(tick_axis),
     color=alt.condition(brush, 'Origin', alt.value('lightgrey'))
 )
 
 y_ticks = base.mark_tick().encode(
-    alt.X('Origin', title='', axis=tick_axis),
-    alt.Y('Horsepower', axis=tick_axis),
+    alt.X('Origin').title('').axis(tick_axis),
+    alt.Y('Horsepower').axis(tick_axis),
     color=alt.condition(brush, 'Origin', alt.value('lightgrey'))
 )