Creating a Multi-Line Tooltip with Altair: A Deep Dive into Customization and Interactivity

Altair Multi-Line Tooltip: A Deep Dive into Customization and Interactivity

Introduction

Altair is a powerful data visualization library in Python that allows users to create a wide range of charts, including line plots, scatter plots, and more. One of the key features of Altair is its ability to handle complex data structures and customize the appearance of the chart. In this article, we will explore how to create a multi-line tooltip using Altair, where each team’s line is highlighted when hovered over.

Problem Statement

The problem presented in the Stack Overflow question is as follows:

We have a dataset with multiple teams and their corresponding statistics.
We want to create a line plot that displays each team’s statistics on separate lines.
When the user hovers over one of the lines, we want to highlight that team’s data point.

Solution Overview

To solve this problem, we can follow these steps:

Create a selection that chooses the nearest point and selects based on x-value.
Create a basic line plot with separate lines for each team.
Add a point layer to display data points for each line, and highlight them when hovered over.
Use Altair’s condition function to conditionally adjust the appearance of the chart.

Creating the Selection

The first step is to create a selection that chooses the nearest point and selects based on x-value. We can do this using the following code:

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

Creating the Basic Line Plot

Next, we create a basic line plot with separate lines for each team:

# The basic line
line = alt.Chart(df_teams_full_stats).mark_line(interpolate='basis').encode(
    x='GameWeek:Q',
    y='Goals:Q',
    color=alt.Color('Color', scale=None)
)

Adding the Point Layer

Now, we add a point layer to display data points for each line and highlight them when hovered over:

# 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, 'Goals:Q', alt.value(' '))
)

Creating the Hover Legend

To create a hover legend that displays each team’s data point, we can use the following code:

# Separate chart to act as a legend
s2 = pd.DataFrame(source.series.unique(), columns=['series'])

hover_legend = alt.Chart(s2).mark_circle(size=100).encode(
    alt.Y('series:N', axis=alt.Axis(orient='right', domain=False, ticks=False), title=None),
    alt.Color('series:N', scale=alt.Scale(scheme='category20b'), legend=None),
    opacity=alt.condition(selection, alt.value(1), alt.value(0.2))
).add_selection(selection)

Combining the Charts

Finally, we combine the line plot and hover legend using the | operator:

# Put the five layers into a chart and bind the data
chart = alt.layer(
    line, points, text, hover_legend
).properties(
    width=1000, height=300
)

Conclusion

In this article, we explored how to create a multi-line tooltip using Altair. We created a selection that chose the nearest point and selected based on x-value, and used this selection to conditionally adjust the appearance of the chart. Additionally, we created a separate hover legend chart that displayed each team’s data point when hovered over. By following these steps, you can create custom charts with interactive elements using Altair.

Additional Resources

Last modified on 2024-03-20