Li Ai
Li Ai

Reputation: 211

Dual axes for y with Altair

I'm trying to create an interactive plot with dual axes. For example, I want to use two axes for y1 and y2 as they have different magnitude:

import altair as alt
import pandas as pd
import numpy as np

np.random.seed(42)
source = pd.DataFrame(np.cumsum(np.random.randn(100, 1), 0).round(2),
                    columns=['A'], index=pd.RangeIndex(100, name='x'))
source = source.reset_index().melt('x', var_name='category', value_name='y1')
source['Type'] = 'First'

source_1 = source.copy()
source_1['y1'] = source_1['y1'] + 5
source_1['Type'] = 'Second'

source_2 = source.copy()
source_2['y1'] = source_2['y1'] - 5
source_2['Type'] = 'Third'

source = pd.concat([source, source_1, source_2])

source['y2'] = source['y1']/10

def singleY_chart(y):

    input_dropdown = alt.binding_select(options=['First', 'Second', 'Third'])
    selection = alt.selection_single(name='Select', fields=['Type'],
                                       bind=input_dropdown)

    # Create a selection that chooses the nearest point & selects based on x-value
    nearest = alt.selection(type='single', nearest=True, on='mouseover',
                            fields=['x'], empty='none')

    # The basic line
    base = alt.Chart(source).encode(
        alt.X('x:Q'),
        alt.Y(y, type='quantitative')
    ).transform_filter(selection)

    # add drop-down menu
    line = base.mark_line().add_selection(selection)

    # Transparent selectors across the chart. This is what tells us
    # the x-value of the cursor
    selectors = alt.Chart(source).mark_point().encode(
        x='x:Q',
        opacity=alt.value(0),
    ).add_selection(
        nearest
    )

    # Draw points on the line, and highlight based on selection
    points = base.mark_point().encode(
        opacity=alt.condition(nearest, alt.value(1), alt.value(0))
    )

    # Draw text labels near the points, and highlight based on selection
    text = base.mark_text(align='left', dx=5, dy=-5).encode(
        text=alt.condition(nearest, alt.Y(y, type='quantitative'), alt.value(' '))
    )

    # Draw a rule at the location of the selection
    rules = alt.Chart(source).mark_rule(color='gray').encode(
        x='x:Q',
    ).transform_filter(
        nearest
    )

    # Put the five layers into a chart and bind the data
    chart = alt.layer(
        line, selectors, points, rules, text
    ).properties(
        width=500, height=300
    ).configure_axisX(
        labelAngle=0
    ).configure_axis(
        titleFontSize=12.5,
        labelFontSize=12.5
    ).configure_legend(
        titleFontSize=12.5,
        labelFontSize=12.5
    )

    return chart


singleY_chart('y1') 
# singleY_chart('y2')

The code above works for y1 or y2 separately. Now I want to plot y1 on the left y-axis and y2 on the right y-axis in the same plot, while being able to show the values of y1 and y2 the same time when I move my mouse on the plot. I searched online and found I might need to use resolve_scale() but I cannot figure out how I should use that.

EDIT: I tried the following code:

import altair as alt
import pandas as pd
import numpy as np

np.random.seed(42)
source = pd.DataFrame(np.cumsum(np.random.randn(100, 1), 0).round(2),
                    columns=['A'], index=pd.RangeIndex(100, name='x'))
source = source.reset_index().melt('x', var_name='category', value_name='y1')
source['Type'] = 'First'

source_1 = source.copy()
source_1['y1'] = source_1['y1'] + 5
source_1['Type'] = 'Second'

source_2 = source.copy()
source_2['y1'] = source_2['y1'] - 5
source_2['Type'] = 'Third'

source = pd.concat([source, source_1, source_2])

source['y2'] = source['y1']/10 + np.random.randn(300, )/10

def singleY_chart():

    input_dropdown = alt.binding_select(options=['First', 'Second', 'Third'])
    selection = alt.selection_single(name='Select', fields=['Type'],
                                       bind=input_dropdown)

    # Create a selection that chooses the nearest point & selects based on x-value
    nearest = alt.selection(type='single', nearest=True, on='mouseover',
                            fields=['x'], empty='none')

    # The basic line
    base = alt.Chart(source).encode(
        alt.X('x:Q')
    ).transform_filter(selection)

    # add drop-down menu
    line_1 = base.mark_line().encode(alt.Y('y1'),
                              color=alt.value('red')).add_selection(selection)

    line_2 = base.mark_line().encode(alt.Y('y2'),
                              color=alt.value('blue'))

    # Transparent selectors across the chart. This is what tells us
    # the x-value of the cursor
    selectors = alt.Chart(source).mark_point().encode(
        x='x:Q',
        opacity=alt.value(0),
    ).add_selection(
        nearest
    )

    # Draw points on the line, and highlight based on selection
    points = base.mark_point().encode(
        opacity=alt.condition(nearest, alt.value(1), alt.value(0))
    )

    # Draw text labels near the points, and highlight based on selection
    text = base.mark_text(align='left', dx=5, dy=-5).encode(
        text=alt.condition(nearest, alt.Y('y2:Q'), alt.value(' '))
    )

    # Draw a rule at the location of the selection
    rules = alt.Chart(source).mark_rule(color='gray').encode(
        x='x:Q',
    ).transform_filter(
        nearest
    )

    # Put the five layers into a chart and bind the data
    chart = alt.layer(
        line_1, line_2, selectors, points, rules, text 
    ).resolve_scale(
    y='independent'
    ).properties(
        width=500, height=300
    ).configure_axisX(
        labelAngle=0
    ).configure_axis(
        titleFontSize=12.5,
        labelFontSize=12.5
    ).configure_legend(
        titleFontSize=12.5,
        labelFontSize=12.5
    )

    return chart


singleY_chart()

This works to some extent but I have the following problems:

  1. since only x is selected in the base the interactive plot only shows points on the x-axis instead of on the lines;
  2. only the y-value of one line (other than both) is shown as specified in the points() and text;
  3. How can I create legends for the two lines?

I'm thinking about melting the y1 and y2 into one column. Will that make it easier to do what I want?

Upvotes: 2

Views: 6610

Answers (1)

bayesways
bayesways

Reputation: 53

I believe resolve_scale is what you need.

Put your chart in "()" and then .resolve_scale(y='independent') as in this example from the docs.

Upvotes: 4

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