如何将系列特定线 y=x 添加到 Altair 中的多面（或类似）双轴图表？

Question

y=x关于如何在使用 Altair时对双轴图表进行分面，然后向每个图表添加一条线，有什么建议吗？挑战在于，该线y=x需要与每个多面图表中显示的数据特定的系列比例相匹配。链接：Altair github 关于 Facets 的问题线程Altair github 轴显示上的问题线程下面是重现该问题的代码。import altair as altfrom vega_datasets import datasource = data.anscombe().copy()source['line-label'] = 'x=y'source = pd.concat([source,source.groupby('Series').agg(x_diff=('X','diff'), y_diff=('Y','diff'))],axis=1)source['rate'] = source.y_diff/source.x_diffsource['rate-label'] = 'rate-of-change'base = alt.Chart().encode(    x='X:O',)scatter = base.mark_circle(size=60, opacity=0.30).encode(    y='Y:Q',    color=alt.Color('Series:O', scale=alt.Scale(scheme='category10')),    tooltip=['Series','X','Y'])line_x_equals_y = alt.Chart().mark_line(color= 'black', strokeDash=[3,8]).encode(    x=alt.X('max(X)',axis=None),    y=alt.Y('max(X)',axis=None), # note: it's intentional to set max(X) here so that X and Y are equal.    color = alt.Color('line-label') # note: the intent here is for the line label to show up in the legend    )rate = base.mark_line(strokeDash=[5,3]).encode(    y=alt.Y('rate:Q'),    color = alt.Color('rate-label',),    tooltip=['rate','X','Y'])scatter_rate = alt.layer(scatter, rate, data=source)尝试过的解决方案问题：图表不是双轴（并且这不包括line_x_equals_y）scatter_rate.facet('Series',columns=2).resolve_axis(         x='independent',         y='independent',         )问题：Javascript 错误alt.layer(scatter_rate, line_x_equals_y, data=source).facet('Series',columns=2).resolve_axis(        x='independent',        y='independent',        )问题：Javascript 错误chart_generator =  (alt.layer(line_x_equals_y, scatter_rate, data = source, title=f"Series {val}").transform_filter(alt.datum.Series == val).resolve_scale(y='independent',x='independent') \             for val in source.Series.unique()) alt.concat(*(    chart_generator), columns=2)目标scatter_rate是一个多面（按系列）双轴图表，带有适合值范围的单独刻度。y=x每个多面图表都包含一条从 (0,0) 到y=max(X)各个图表的值的线。

Answer 1

您可以通过正常创建图层并调用facet()图层图表上的方法来完成此操作。唯一的要求是所有层共享相同的源数据；无需手动构建facet，并且在当前版本的Altair中无需为facet进行后期数据绑定：

import altair as alt

from vega_datasets import data

import pandas as pd

source = data.anscombe().copy()

source['line-label'] = 'x=y'

source = pd.concat([source,source.groupby('Series').agg(x_diff=('X','diff'), y_diff=('Y','diff'))],axis=1)

source['rate'] = source.y_diff/source.x_diff

source['rate-label'] = 'line y=x'

source_linear = source.groupby(by=['Series']).agg(x_linear=('X','max'), y_linear=('X', 'max')).reset_index().sort_values(by=['Series'])

source_origin = source_linear.copy()

source_origin['y_linear'] = 0

source_origin['x_linear'] = 0

source_linear = pd.concat([source_origin,source_linear]).sort_values(by=['Series'])

source = source.merge(source_linear,on='Series').drop_duplicates()

scatter = alt.Chart(source).mark_circle(size=60, opacity=0.60).encode(

    x='X:Q',

    y='Y:Q',

    color='Series:N',

    tooltip=['X','Y','rate']

)

rate = alt.Chart(source).mark_line(strokeDash=[5,3]).encode(

    x='X:Q',

    y='rate:Q',

    color = 'rate-label:N'

)

line_plot = alt.Chart(source).mark_line(color= 'black', strokeDash=[3,8]).encode(

    x=alt.X('x_linear', title = ''),

    y=alt.Y('y_linear', title = ''),

    shape = alt.Shape('rate-label', title = 'Break Even'),

    color = alt.value('black')

)

alt.layer(scatter, rate, line_plot).facet(

    'Series:N'

).properties(

    columns=2

).resolve_scale(

    x='independent',

    y='independent'

)

Answer 2

y=x该解决方案为每个图表上的数据按比例构建所需的线；但是，点在合并步骤中重复，我不确定如何添加双轴速率。

获取数据

source = data.anscombe().copy()

source['line-label'] = 'x=y'

source = pd.concat([source,source.groupby('Series').agg(x_diff=('X','diff'), y_diff=('Y','diff'))],axis=1)

source['rate'] = source.y_diff/source.x_diff

source['rate-label'] = 'line y=x'

创建Y=X线数据

source_linear = source.groupby(by=['Series']).agg(x_linear=('X','max'), y_linear=('X', 'max')).reset_index().sort_values(by=['Series'])

source_origin = source_linear.copy()

source_origin['y_linear'] = 0

source_origin['x_linear'] = 0

source_linear = pd.concat([source_origin,source_linear]).sort_values(by=['Series'])

合并线性数据

source = source.merge(source_linear,on='Series').drop_duplicates()

构建图表

scatter = alt.Chart().mark_circle(size=60, opacity=0.60).encode(

    x=alt.X('X', title='X'),

    y=alt.Y('Y', title='Y'),

    #color='year:N',

    tooltip=['X','Y','rate']

)

line_plot = alt.Chart().mark_line(color= 'black', strokeDash=[3,8]).encode(

    x=alt.X('x_linear', title = ''),

    y=alt.Y('y_linear', title = ''),

    shape = alt.Shape('rate-label', title = 'Break Even'),

    color = alt.value('black')

)

手动分面图

chart_generator =  (alt.layer(scatter, line_plot, data = source, title=f"{val}: Duplicated Points w/ Line at Y=X").transform_filter(alt.datum.Series == val) \

             for val in source.Series.unique())

组合图表

chart = alt.concat(*(

    chart_generator

), columns=3)

chart.display()

Answer 3

该解决方案包括速率，但不是Y一个轴和rate另一个轴上的双轴。

import altair as alt

from vega_datasets import data

import pandas as pd

source = data.anscombe().copy()

source['line-label'] = 'x=y'

source = pd.concat([source,source.groupby('Series').agg(x_diff=('X','diff'), y_diff=('Y','diff'))],axis=1)

source['rate'] = source.y_diff/source.x_diff

source['rate-label'] = 'rate of change'

source['line-label'] = 'line y=x'

source_linear = source.groupby(by=['Series']).agg(x_linear=('X','max'), y_linear=('X', 'max')).reset_index().sort_values(by=['Series'])

source_origin = source_linear.copy()

source_origin['y_linear'] = 0

source_origin['x_linear'] = 0

source_linear = pd.concat([source_origin,source_linear]).sort_values(by=['Series'])

source = source.merge(source_linear,on='Series').drop_duplicates()

scatter = alt.Chart(source).mark_circle(size=60, opacity=0.60).encode(

    x=alt.X('X', title='X'),

    y=alt.Y('Y', title='Y'),

    color='Series:N',

    tooltip=['X','Y','rate']

)

line_plot = alt.Chart(source).mark_line(color= 'black', strokeDash=[3,8]).encode(

    x=alt.X('x_linear', title = ''),

    y=alt.Y('y_linear', title = ''),

    shape = alt.Shape('line-label', title = 'Break Even'),

    color = alt.value('black')

)

rate =  alt.Chart(source).mark_line(strokeDash=[5,3]).encode(

    x=alt.X('X', axis=None, title = 'X'),

    y=alt.Y('rate:Q'),

    color = alt.Color('rate-label',),

    tooltip=['rate','X','Y']

)

alt.layer(scatter, line_plot, rate).facet(

    'Series:N'

).properties(

    columns=2

).resolve_scale(

    x='independent',

    y='independent'

).display()