如何构建带双轴的 Altair 分层图表?
How to build an Altair layered chart w/ dual axis?
描述
此代码显示三个 Altair 图表:
scatter
rate
line_plot
目标
目标是将所有图表组合成具有以下规范的分层图表:
- 显示
scatter
和 rate
的 y 轴(即双轴图表)
- 方面
Series
- 显示
line_plot
.
代码
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', title = 'X'),
y=alt.Y('rate:Q'),
color = alt.Color('rate-label',),
tooltip=['rate','X','Y']
)
当前解决方案
当前解决方案的问题是 rate
图表的 y 轴未显示为双轴。有什么建议吗?
alt.layer(rate,scatter,line_plot).facet(
'Series:N'
, columns=2
).resolve_scale(
x='independent',
y='independent'
).display()
好吧,我知道了,但这可能不是最好的解决方案。我已按照以下 link 中描述的方法手动对图表进行分面:
为了获得双轴,我刚刚在手动步骤中添加了.resolve_scale(y='independent')
。以下是解决方案:
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().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().mark_line(color= 'black', strokeDash=\[3,8\]).encode(
x=alt.X('x_linear', title = '', axis=None),
y=alt.Y('y_linear', title = '', axis=None),
shape = alt.Shape('line-label', title = 'Break Even'),
color = alt.value('black')
)
rate = alt.Chart().mark_line(strokeDash=\[5,3\]).encode(
x=alt.X('X', title = 'X'),
y=alt.Y('rate:Q'),
color = alt.Color('rate-label',),
tooltip=\['rate','X','Y'\]
)
scatter_rate = alt.layer(scatter, rate, data=source)
chart_generator = (alt.layer(scatter, rate, line_plot, data = source, title=f"{val}: Duplicated Points w/ Line at Y=X").transform_filter(alt.datum.Series == val).resolve_scale(y='independent') \
for val in source.Series.unique())
chart = alt.concat(*(
chart_generator
), columns=2).display()
描述
此代码显示三个 Altair 图表:
scatter
rate
line_plot
目标
目标是将所有图表组合成具有以下规范的分层图表:
- 显示
scatter
和rate
的 y 轴(即双轴图表) - 方面
Series
- 显示
line_plot
.
代码
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', title = 'X'),
y=alt.Y('rate:Q'),
color = alt.Color('rate-label',),
tooltip=['rate','X','Y']
)
当前解决方案
当前解决方案的问题是 rate
图表的 y 轴未显示为双轴。有什么建议吗?
alt.layer(rate,scatter,line_plot).facet(
'Series:N'
, columns=2
).resolve_scale(
x='independent',
y='independent'
).display()
好吧,我知道了,但这可能不是最好的解决方案。我已按照以下 link 中描述的方法手动对图表进行分面:
为了获得双轴,我刚刚在手动步骤中添加了.resolve_scale(y='independent')
。以下是解决方案:
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().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().mark_line(color= 'black', strokeDash=\[3,8\]).encode(
x=alt.X('x_linear', title = '', axis=None),
y=alt.Y('y_linear', title = '', axis=None),
shape = alt.Shape('line-label', title = 'Break Even'),
color = alt.value('black')
)
rate = alt.Chart().mark_line(strokeDash=\[5,3\]).encode(
x=alt.X('X', title = 'X'),
y=alt.Y('rate:Q'),
color = alt.Color('rate-label',),
tooltip=\['rate','X','Y'\]
)
scatter_rate = alt.layer(scatter, rate, data=source)
chart_generator = (alt.layer(scatter, rate, line_plot, data = source, title=f"{val}: Duplicated Points w/ Line at Y=X").transform_filter(alt.datum.Series == val).resolve_scale(y='independent') \
for val in source.Series.unique())
chart = alt.concat(*(
chart_generator
), columns=2).display()