hastyplot 0.4.1

Hasty plotting for Altair, inspired by ggplot2's qplot

hastyplot

This library is completely generated from a marimo notebook.

You can inspect the full implementation/docs/demo/test suite be clicking the button below.

Hasty plotting for Altair, inspired by ggplot2's qplot.

from hastyplot import qplot

# Scatter plot
qplot(df, "x", "y")

# Histogram (x-only)
qplot(df, "x")

# With pipe
df.pipe(qplot, "x", "y", color="group")

Install

uv add hastyplot

Examples

# Scatter with color and smooth
qplot(cars, "Horsepower", "Miles_per_Gallon",
      color="Origin", smooth="loess",
      title="HP vs MPG", theme="minimal")

# Boxplot
qplot(cars, "Origin", "Miles_per_Gallon", mark="boxplot")

# Matrix / heatmap from long-table data
qplot(matrix_df, "col", "row", mark="rect", color="value")

# Faceted scatter
qplot(cars, "Horsepower", "Miles_per_Gallon",
      facet_wrap="Cylinders", columns=3, width=200, height=150)

# Lines grouped without color
qplot(stocks, "date", "price", mark="line", group="symbol")

# Lines grouped with a fixed color
qplot(stocks, "date", "price", mark="line", group="symbol", color="#red")

# Histogram with custom bins
qplot(cars, "Horsepower", bins=20, theme="clean")

# Area chart
qplot(stocks, "date", "price", mark="area", color="symbol")

# Step chart
qplot(stocks, "date", "price", mark="step", color="symbol")

# With axis limits and tooltip
qplot(cars, "Horsepower", "Miles_per_Gallon",
      x_lim=(0, 250), y_lim=(None, 40),
      tooltip=["Name", "Origin"])

# Polynomial smooth
qplot(cars, "Horsepower", "Miles_per_Gallon", smooth="poly")

Themes

Pass the theme parameter to change the look of any chart:

qplot(df, "x", "y", theme="clean")

• "default" — Altair's built-in styling, no customization applied.
• "clean" — No gridlines, dark axis colors, system-ui fonts, bold title.
• "minimal" — Light gridlines, no axis domain lines, Libre Franklin / Helvetica Neue fonts, bottom-oriented legend, and a custom color palette.

API

There is only one function and it is called qplot. In this function data is the first argument so you can use df.pipe(qplot, "x", "y"). Here's all the input options:

Data & axes

• data — DataFrame to plot.
• x — column for the x-axis.
• y — column for the y-axis. Omit for a histogram.
• x_lim / y_lim — axis limits as (min, max) tuples. Use None for an open bound.
• tooltip — list of column names to show on hover.

Aesthetics

• color — column to map to color. Use "#red" for a fixed named color value, or "#ff0000" for a fixed hex color.
• size — column to map to point size.
• opacity — a fixed float (e.g. 0.5) or a column name.
• group — column to group by without changing color. Useful for separate lines per group in a uniform color.

Mark & smoothing

• mark — options: "scatter", "circle", "line", "bar", "boxplot", "hist", "area", "step", "rect".
• smooth — overlay a trend line: "loess", "linear", "poly", "log", "exp", "pow".
• bandwidth — loess bandwidth, 0 to 1 (default 0.3). Lower = wigglier.
• bins — number of histogram bins. Omit for Altair's default.

Faceting

• facet_col / facet_row — column names for a facet grid.
• facet_wrap — single column, wraps into rows.
• columns — max columns before wrapping (default 3).

Layout & appearance

• width / height — chart size in pixels (per panel when faceted).
• title / subtitle — chart title and subtitle.
• theme — "default", "clean", or "minimal".
• actions — show the Vega-Lite export menu (default False).