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Interactive Charts in Jupyter Notebooks

Jupyter is where most analysis starts. Vizly charts render inline automatically because chart objects implement _repr_html_(). Create a chart, and it displays in the cell output. No special display calls, no magic.

Basic inline chart​

import vizly as vz

data = [
    {"date": "2026-01-01", "revenue": 42},
    {"date": "2026-01-02", "revenue": 48},
    {"date": "2026-01-03", "revenue": 45},
]

vz.set_theme("corporate")
vz.line(data, x="date", y="revenue", title="Revenue")

The chart appears below the cell, fully interactive: tooltips, zoom, and legend toggles all work in the notebook output.

Choosing a theme per chart​

You can set a session theme, or override it per chart with the theme= kwarg.

vz.set_theme("dark")

vz.bar(data, x="date", y="revenue", title="Dark theme")
vz.bar(data, x="date", y="revenue", title="Editor theme", theme="editor_tokyo_night")

Working with pandas​

Pass DataFrames directly to chart factories. This is the natural notebook flow: load, transform, chart.

import pandas as pd
import vizly as vz

df = pd.DataFrame({
    "date": ["2026-01-01", "2026-01-02", "2026-01-03", "2026-01-04", "2026-01-05"],
    "revenue": [42, 48, 45, 61, 58],
    "cost": [18, 20, 19, 24, 22],
})

vz.line(df, x="date", y=["revenue", "cost"], title="Revenue vs cost")

Capturing the HTML for reuse​

If you need the raw HTML instead of relying on inline display, call to_html() or write it to a file with render().

html = chart.to_html()
chart.render("chart.html")  # writes a self-contained file

SQL directly in a notebook​

Use from_sql to pull data into a chart without manual DataFrames.

from sqlalchemy import create_engine

engine = create_engine("sqlite:///sales.db")
table = vz.from_sql("SELECT region, SUM(sales) AS sales FROM orders GROUP BY region", bind=engine)
vz.bar(table, x="region", y="sales", title="Sales by region")

Comparing several charts in one cell​

For a quick comparison view, compose charts into a grid or tab layout and display it as one output.

vz.set_theme("corporate")

chart = vz.grid(
    charts=[
        vz.bar(df, x="date", y="revenue", title="Revenue"),
        vz.line(df, x="date", y="cost", title="Cost"),
    ],
    title="Comparison",
)
chart  # renders as one grid in the cell

Tips​

TipDetail
Just create the chartA chart object as the last expression in a cell renders automatically.
Set a session themevz.set_theme("dark") once at the top of the notebook applies to all later charts.
Compose for comparisonsvz.grid and vz.tab let several charts share one cell output and one ECharts load.
Save to HTMLUse chart.render("out.html") to export any notebook chart for sharing or embedding.