如何在Altair中向多面或类似双轴图表添加特定于系列的线y = x？ 问题：图表不是双轴的并且不包括line_x_equals_y问题：JavaScript错误问题：JavaScript错误获取数据创建Y = X行数据合并线性数据构建图表手动分面图合并图表

如何解决如何在Altair中向多面或类似双轴图表添加特定于系列的线y = x？ 问题：图表不是双轴的并且不包括line_x_equals_y问题：JavaScript错误问题：JavaScript错误获取数据创建Y = X行数据合并线性数据构建图表手动分面图合并图表

关于如何制作双轴图表，然后使用Altair在y=x的每个图表上添加一条线的任何建议？挑战在于，y=x行必须与特定于每个多面图表中显示的数据的系列比例相匹配。

链接：

1. altair github issue thread on facets
2. altair github issue thread on axis display

下面是重现该问题的代码。

import altair as alt
from vega_datasets import data

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'


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)',# 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','Y']
)

scatter_rate = alt.layer(scatter,rate,data=source)

尝试的解决方案

问题：图表不是双轴的（并且不包括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',)

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

1. 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。
2. 每个多面图表均包含一行y=x，其范围从单个图表的（0,0）到y=max(X)值。

解决方法

您可以通过正常创建图层并在图层表上调用facet()方法来做到这一点。唯一的要求是所有层共享相同的源数据。在当前版本的Altair中，无需手动构造构面，也不需要后期的数据绑定：

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',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'
)

,

此解决方案在y=x处根据每个图表上的数据构建所需的线；但是，点在合并步骤中是重复的，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,axis=1)
source['rate'] = source.y_diff/source.x_diff
source['rate-label'] = 'line y=x'

创建Y = X行数据

source_linear = source.groupby(by=['Series']).agg(x_linear=('X',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','rate']
)

line_plot = alt.Chart().mark_line(color= 'black',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())

合并图表

chart = alt.concat(*(
    chart_generator
),columns=3)

chart.display()

,

此解决方案包括费率，但不是双轴w / Y和另一轴rate。

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,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','rate']
)

line_plot = alt.Chart(source).mark_line(color= 'black',shape = alt.Shape('line-label',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,rate).facet(
    'Series:N'
).properties(
    columns=2
).resolve_scale(
    x='independent',y='independent'
).display()