Altair:使用字段指定 Y 轴的域?
Altair: use a field to specify the domain of the Y axis?
是否可以使用数据中的字段来指定Y轴的域?
我试过类似的方法,但没有用:
scale=alt.Scale(domain = ['field1','field2'])
假设我有一个像下面这样的交互式绘图,我希望 Y 轴域随着图例中的选择而改变。
import altair as alt
from vega_datasets import data
source = data.unemployment_across_industries.url
source = pd.read_json(source)
source['field1'] = 0
source['field2'] = 20000
selection = alt.selection_multi(fields=['series'], bind='legend')
alt.Chart(source).mark_area().encode(
alt.X('yearmonth(date):T', axis=alt.Axis(domain=False, format='%Y', tickSize=0)),
alt.Y('sum(count):Q', stack='center', scale=alt.Scale(domain = ['field1','field2'])),
alt.Color('series:N', scale=alt.Scale(scheme='category20b')),
opacity=alt.condition(selection, alt.value(1), alt.value(0.2))
).add_selection(
selection
)
不行,domain
只能设置成一对数字。如果您希望域响应选择,一种方法是使用不带显式域的过滤器转换。例如:
source = data.unemployment_across_industries.url
selection = alt.selection_multi(fields=['series'], bind='legend')
alt.Chart(source).mark_area().encode(
alt.X('yearmonth(date):T', axis=alt.Axis(domain=False, format='%Y', tickSize=0)),
alt.Y('sum(count):Q', stack='center'),
alt.Color('series:N', scale=alt.Scale(scheme='category20b'))
).add_selection(
selection
).transform_filter(selection)
是否可以使用数据中的字段来指定Y轴的域?
我试过类似的方法,但没有用:
scale=alt.Scale(domain = ['field1','field2'])
假设我有一个像下面这样的交互式绘图,我希望 Y 轴域随着图例中的选择而改变。
import altair as alt
from vega_datasets import data
source = data.unemployment_across_industries.url
source = pd.read_json(source)
source['field1'] = 0
source['field2'] = 20000
selection = alt.selection_multi(fields=['series'], bind='legend')
alt.Chart(source).mark_area().encode(
alt.X('yearmonth(date):T', axis=alt.Axis(domain=False, format='%Y', tickSize=0)),
alt.Y('sum(count):Q', stack='center', scale=alt.Scale(domain = ['field1','field2'])),
alt.Color('series:N', scale=alt.Scale(scheme='category20b')),
opacity=alt.condition(selection, alt.value(1), alt.value(0.2))
).add_selection(
selection
)
不行,domain
只能设置成一对数字。如果您希望域响应选择,一种方法是使用不带显式域的过滤器转换。例如:
source = data.unemployment_across_industries.url
selection = alt.selection_multi(fields=['series'], bind='legend')
alt.Chart(source).mark_area().encode(
alt.X('yearmonth(date):T', axis=alt.Axis(domain=False, format='%Y', tickSize=0)),
alt.Y('sum(count):Q', stack='center'),
alt.Color('series:N', scale=alt.Scale(scheme='category20b'))
).add_selection(
selection
).transform_filter(selection)