Skip to content
Advertisement

How to label the line from transform_regression using Altair?

The code below creates a regression line; however, the legend defaults to labeling the line as “undefined.” How can this regression line be labeled in the legend as “reg-line”?

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'

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']
)

scatter = scatter + scatter.transform_regression('X', 'Y').mark_line(opacity=0.50, shape='mark')

chart = scatter.facet(
    columns=2
    , facet=alt.Facet('Series',header=alt.Header(labelFontSize=25))
).resolve_scale(
    x='independent',
    y='independent'
)

chart.display()

enter image description here

Advertisement

Answer

Simply add .transform_fold(["reg-line"], as_=["Regression", "y"]).encode(alt.Color("Regression:N")) after mark line

Code should look like

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'

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']
)

scatter = scatter + scatter.transform_regression('X', 'Y').mark_line(
     opacity=0.50, 
     shape='mark'
).transform_fold(
     ["reg-line"], 
     as_=["Regression", "y"]
).encode(alt.Color("Regression:N"))
chart = scatter.facet(
    columns=2
    , facet=alt.Facet('Series',header=alt.Header(labelFontSize=25))
).resolve_scale(
    x='independent',
    y='independent'
)

chart.display()

enter image description here

User contributions licensed under: CC BY-SA
6 People found this is helpful
Advertisement