Multi-Line Tooltip

This example shows how you can use selections and layers to create a tooltip-like behavior tied to the x position of the cursor. If you are looking for more standard tooltips, it is recommended to use the tooltip encoding channel as shown in the Scatter Plot With Tooltips example.

The following example employs a little trick to isolate the x-position of the cursor: we add some transparent points with only an x encoding (no y encoding) and tie a nearest selection to these, tied to the “x” field.

Method syntax

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, 3), 0).round(2),
    columns=['A', 'B', 'C'], index=pd.RangeIndex(100, name='x')
)
source = source.reset_index().melt('x', var_name='category', value_name='y')

# Create a selection that chooses the nearest point & selects based on x-value
nearest = alt.selection_point(nearest=True, on='mouseover',
                        fields=['x'], empty=False)

# The basic line
line = alt.Chart(source).mark_line(interpolate='basis').encode(
    x='x:Q',
    y='y:Q',
    color='category:N'
)

# 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_params(
    nearest
)

# Draw points on the line, and highlight based on selection
points = line.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 = line.mark_text(align='left', dx=5, dy=-5).encode(
    text=alt.condition(nearest, 'y: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
alt.layer(
    line, selectors, points, rules, text
).properties(
    width=600, height=300
)

Attribute syntax

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, 3), 0).round(2),
                    columns=['A', 'B', 'C'], index=pd.RangeIndex(100, name='x'))
source = source.reset_index().melt('x', var_name='category', value_name='y')

# Create a selection that chooses the nearest point & selects based on x-value
nearest = alt.selection_point(nearest=True, on='mouseover',
                        fields=['x'], empty=False)

# The basic line
line = alt.Chart(source).mark_line(interpolate='basis').encode(
    x='x:Q',
    y='y:Q',
    color='category:N'
)

# 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_params(
    nearest
)

# Draw points on the line, and highlight based on selection
points = line.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 = line.mark_text(align='left', dx=5, dy=-5).encode(
    text=alt.condition(nearest, 'y: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
alt.layer(
    line, selectors, points, rules, text
).properties(
    width=600, height=300
)