Python Academy · Lesson

Interactive Features

Zoom, hover, and pan.

Interactive Features is a free Python Academy lesson on CoddyKit — lesson 2 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Python Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.

Why Interactivity Matters

The biggest advantage of Plotly over static libraries is that charts respond to the user. Readers can zoom into a region, pan across data, and hover to read exact values without you crowding the chart with labels.

Interactivity lets one chart serve both the overview and the detail.

Hover Tooltips

By default, hovering a point shows its x and y values. You can enrich this with hover_data=['col1', 'col2'] to add extra columns, or hover_name='name' to set the bold title of the tooltip.

Good tooltips remove the need for clutter on the plot itself.

Building a Tooltip String

Conceptually a tooltip is just formatted text assembled from a row of data. Here is the same idea in plain Python.

point = {'name': 'Berlin', 'pop': 3700000, 'gdp': 154}
tooltip = point['name'] + '\nPop: ' + format(point['pop'], ',') + '\nGDP: ' + str(point['gdp'])
print(tooltip)

Zoom and Pan

Plotly figures include a mode bar with zoom, pan, and box-select tools. Users can also drag to zoom into a rectangle and double-click to reset.

These behaviors are on by default; you usually do not write any code for them.

The Range and Reset

Zooming changes the axis range temporarily. You can set the initial range with fig.update_xaxes(range=[0, 100]), and the user can always reset to it.

Think of zoom as choosing a sub-window of the full data range.

full_min, full_max = 0, 1000
zoom_min, zoom_max = 200, 400
visible = zoom_max - zoom_min
total = full_max - full_min
print('Zoom shows', round(visible / total * 100), '% of the range')

Hover Modes

fig.update_layout(hovermode='x unified') shows a single tooltip listing every series at the hovered x position. This is excellent for comparing multiple lines at the same point in time.

Other modes include 'closest' and 'x'.

Legend Interactivity

Plotly legends are clickable. A single click hides a series; a double click isolates it. This lets users focus on the data they care about without you building separate charts.

It works automatically whenever your chart has multiple traces.

Range Sliders

For time series, add a range slider with fig.update_xaxes(rangeslider_visible=True). A small overview chart appears below, letting users drag to select a window of dates.

It pairs well with range selector buttons like 1m, 6m, YTD.

Custom Hover Templates

For full control use hovertemplate, a string with placeholders like %{x} and %{y}. You decide the exact text and number formatting shown on hover.

Designing the template is like designing any formatted string.

x, y = 2021, 42.567
template = 'Year %{x}: $%{y:.1f}M'
rendered = template.replace('%{x}', str(x)).replace('%{y:.1f}', format(y, '.1f'))
print(rendered)

Knowing When to Stop

Interactivity is powerful but not free of cost. Too many controls overwhelm casual readers. Enable the features that answer real questions, and rely on the sensible defaults for the rest.

The Mode Bar

The toolbar in the top-right of every figure is the mode bar. It hosts zoom, pan, autoscale, and a camera button to download a PNG. You can configure or hide it with the config argument when displaying the figure.

Hiding unused buttons declutters the chart for non-technical audiences.

Quick Check

Test your knowledge of interactive features.

Recap

You explored Plotly interactivity:

Hover tooltips, enriched with hover_data and hovertemplate
Zoom and pan via the built-in mode bar
hovermode='x unified' for combined tooltips
Clickable legends and time-series range sliders

Use these features deliberately to answer real questions.

Frequently asked questions

Is the “Interactive Features” lesson free?

Yes — the full text of “Interactive Features” is free to read here on the web, and the Python Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Python Academy course, upgrade to CoddyKit PRO.

What will I learn in “Interactive Features”?

Zoom, hover, and pan. You practise Python Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.

Do I need any experience to start Python Academy?

No prior experience is required. Python Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 2 of 4, so you can start here or from the beginning and move at your own pace.

How long does the “Interactive Features” lesson take?

Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.

Can I write and run code in this Python Academy lesson?

Yes. Every Python Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.

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