Annotated Scatter Plot with Text Labels — Altair

A scatter plot where each data point can have a text label annotation, useful for identifying specific points of interest. This visualization enhances basic scatter plots by adding contextual information directly on the chart, making it easy to highlight outliers, named entities, or key data points that deserve special attention.

Annotated Scatter Plot with Text Labels rendered with Altair

Python source (Altair)

""" anyplot.ai
scatter-annotated: Annotated Scatter Plot with Text Labels
Library: altair 6.1.0 | Python 3.13.13
Quality: 88/100 | Updated: 2026-05-13
"""

import os

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


THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
BRAND = "#009E73"

# Data - Selected tech companies showing range of revenue/profit metrics
np.random.seed(42)
companies = ["NVIDIA", "Apple", "Microsoft", "Amazon", "Google", "Meta", "Adobe", "Oracle", "Tesla", "Intel"]
# Revenue (billions USD) - realistic values
revenue = np.array([61, 385, 211, 574, 307, 135, 19, 50, 97, 63])
# Profit margin (%) - realistic values
profit_margin = np.array([55, 25, 35, 6, 22, 20, 34, 26, 11, 8])

df = pd.DataFrame({"company": companies, "revenue": revenue, "profit_margin": profit_margin})

# Points layer with Okabe-Ito brand color
points = (
    alt.Chart(df)
    .mark_point(size=250, filled=True, opacity=0.7, color=BRAND)
    .encode(
        x=alt.X("revenue:Q", title="Revenue (Billions USD)", scale=alt.Scale(domain=[0, 620])),
        y=alt.Y("profit_margin:Q", title="Profit Margin (%)", scale=alt.Scale(domain=[0, 60])),
        tooltip=["company:N", "revenue:Q", "profit_margin:Q"],
    )
)

# Connector lines from points to labels
connector_lines = (
    alt.Chart(df)
    .mark_line(size=1, opacity=0.3, color=INK_SOFT)
    .encode(x="revenue:Q", y="profit_margin:Q", x2=alt.X2("revenue:Q"), y2=alt.Y2("profit_margin:Q"))
)

# Text labels layer with theme-adaptive color
labels = (
    alt.Chart(df)
    .mark_text(align="left", dx=12, dy=-8, fontSize=18, fontWeight="bold", color=INK)
    .encode(x=alt.X("revenue:Q"), y=alt.Y("profit_margin:Q"), text="company:N")
)

# Combine layers with theme-adaptive styling
chart = (
    (points + connector_lines + labels)
    .properties(
        width=1600,
        height=900,
        background=PAGE_BG,
        title=alt.Title(text="scatter-annotated · altair · anyplot.ai", fontSize=28, anchor="middle", color=INK),
    )
    .configure_view(strokeWidth=0, fill=PAGE_BG)
    .configure_axis(
        domainColor=INK_SOFT,
        tickColor=INK_SOFT,
        gridColor=INK,
        gridOpacity=0.10,
        labelColor=INK_SOFT,
        labelFontSize=18,
        titleColor=INK,
        titleFontSize=22,
    )
    .configure_title(color=INK)
    .configure_legend(fillColor=ELEVATED_BG, strokeColor=INK_SOFT, labelColor=INK_SOFT, titleColor=INK)
)

# Save as PNG (4800x2700 with scale_factor=3)
chart.save(f"plot-{THEME}.png", scale_factor=3.0)

# Save as HTML for interactivity
chart.save(f"plot-{THEME}.html")

Part of Annotated Scatter Plot with Text Labels on anyplot.ai.

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