kx-plot

One-line matplotlib plots and themes for notebooks and scripts.

kx is a small, plain-Python package with .mplstyle themes, palettes and colourmaps. It needs nothing beyond matplotlib, numpy and pandas and works offline, so it also runs in Kaggle competition notebooks.

Install

pip install kx-plot

import kx; kx.use('dark')

Kaggle

Attach the dataset instead (Add Input → Datasets → vhrabar/kx-plot), then:

import sys; sys.path.append('/kaggle/input/datasets/vhrabar/kx-plot')
import kx; kx.use('dark')

Usage

kx.use('light', palette='okabe', cmap='cividis')   # notebook default: theme, palette, colormap
kx.plot(x, y, z, 'scatter-grid-leg')               # spec: kind-theme-flag-...
kx.plot(x, y, 'bar-paper')                         # a theme in the spec applies to this plot only
with kx.context('paper'): ...                      # or to every plot in the block
kx.save('fig.png')                                 # to /kaggle/working on Kaggle, else the current folder
for ax, col in zip(kx.grid(3), df.columns):        # a figure of 3 panels, a flat array of axes
    kx.plot(df, col, spec='hist', ax=ax)
kx.plot(df, 'month', 'y2025', 'bar')               # DataFrame columns by name
kx.plot(x, y, 'line', linewidth=3)                 # other keywords go to matplotlib
kx.plot(df, 'value', spec='kde', by='group')       # one density curve per group
kx.plot(df.value, spec='box', by=df.group)         # one box per group (also ridge, violin, qq)

stack works with area, bar, barh and hist. norm is a 100% stack for area and a density (area 1) for hist. cum makes hist cumulative; hist-norm-cum is the CDF. hist puts every series on the same bins, so the bars line up.

Unknown tokens raise an error instead of being guessed, with the closest valid tokens as a hint. Everything is inspectable: kx.grammar(), kx.grammar('area'), kx.parse('leg-scatter'), kx.show('dark'), kx.source('scatter').

Tables

kx.load('passengers') is a demo table with numbers, categories and NaNs to try these on.

kx.missing(df)                                     # share of NaNs per column, the most missing on top
kx.plot(df, 'nullmap-sort')                        # where the NaNs are: one pixel row per table row
kx.plot(df, 'heat-corr-ann')                       # correlations of the numeric columns, -1 to 1
kx.plot(df, 'heat')                                # any numeric DataFrame or 2-D array as coloured cells
kx.plot(df, 'pclass', spec='count', by='survived') # rows per category, split by a second column
kx.plot(df, 'pclass', 'port', 'crosstab-norm-ann') # how often each pair of categories occurs
kx.plot(df, 'age', 'fare', 'hexbin-logc')          # points per hexagon; with a z, its mean per hexagon

heat, missing and nullmap take the whole table and no column names; kx.plot(df[cols], 'heat') for some columns. wrap breaks long tick labels onto several lines.

rcParams can be overridden in kx.use with __ for dots: kx.use('dark', figure__figsize=(8, 4)).

Every kind, option, flag and config, with its output, is in the Example Usage notebook.

Palettes

Palettes for kx.use(theme, palette=...), they swap only the colours; a theme's other cycled properties (such as paper's linestyles) stay.

kx.palette('okabe') returns the hex codes. A list of colours works too: palette=['#264653', '#e9c46a'].

Colourmaps

Colourmaps for kx.use(theme, cmap=...) colour continuous values, such as a numeric z in scatter. Without cmap, the theme's own default applies. Add _r to any name to reverse it, e.g. cmap="thermal_r".

kx.cmaps() lists the ones that are available in the installed matplotlib as those implemented in matplotlib 3.10 or newer are not vendored.

License

Released under the MIT License. See LICENSE.

Copyright © 2026 Vedran Hrabar

Vendored palettes and colourmaps keep their own licences; see kx/styles/palettes/LICENCES.md and kx/styles/cmaps/LICENCES.md.