如何在 Altair 的多面（或類似）雙軸圖表中添加特定於系列的線 y=x？

Question

關於如何使用 Altair 對雙軸圖表進行刻面，然后在y=x處向每個圖表添加一條線的任何建議？ 挑戰在於線y=x需要匹配特定於每個分面圖表中顯示的數據的系列的比例。

鏈接：

1. 有關方面的 altair github 問題線程
2. 軸顯示上的 altair github 問題線程

下面是重現該問題的代碼。

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)',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)

嘗試的解決方案

問題：圖表不是雙軸（這不包括line_x_equals_y ）

scatter_rate.facet('Series',columns=2).resolve_axis(
        x='independent',
        y='independent',
        )

問題：Javascript 錯誤

alt.layer(scatter_rate, line_x_equals_y, data=source).facet('Series',columns=2).resolve_axis(
        x='independent',
        y='independent',
        )

問題：Javascript 錯誤

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)

目標

1. scatter_rate是一個分面（按系列）雙軸圖表，帶有適用於值范圍的單獨刻度。
2. 每個分面圖表都包含一條線y=x ，它從單個圖表的 (0,0) 到y=max(X)值。

Answer 1

您可以通過正常創建圖層並在圖層圖表上調用facet()方法來完成此操作。 唯一的要求是所有層共享相同的源數據； 無需手動構建 facet，也無需在當前版本的 Altair 中對 facet 進行后期數據綁定：

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

此解決方案在y=x為每個圖表上的數據構建所需的線； 但是，點在合並步驟中重復，我不確定如何添加雙軸速率。

獲取數據

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'

創建 Y=X 線數據

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'])

合並線性數據

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

構建圖表

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')
)

手動分面圖

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())

組合圖表

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

chart.display()

Answer 3

該解決方案包括速率，但不是一個雙軸，一個軸是Y ，另一個軸是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,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()