class plotnine.geoms.geom_step(mapping: Aes | None = None, data: DataLike | None = None, **kwargs: Any)[source]

Stepped connected points


geom_step(mapping=None, data=None, stat='identity', position='identity',
          na_rm=False, inherit_aes=True, show_legend=None, raster=False,
          direction='hv', **kwargs)

Only the data and mapping can be positional, the rest must be keyword arguments. **kwargs can be aesthetics (or parameters) used by the stat.

mappingaes, optional

Aesthetic mappings created with aes(). If specified and inherit.aes=True, it is combined with the default mapping for the plot. You must supply mapping if there is no plot mapping.


Default value












The bold aesthetics are required.

datadataframe, optional

The data to be displayed in this layer. If None, the data from from the ggplot() call is used. If specified, it overrides the data from the ggplot() call.

statstr or stat, optional (default: stat_identity)

The statistical transformation to use on the data for this layer. If it is a string, it must be the registered and known to Plotnine.

positionstr or position, optional (default: position_identity)

Position adjustment. If it is a string, it must be registered and known to Plotnine.

na_rmbool, optional (default: False)

If False, removes missing values with a warning. If True silently removes missing values.

inherit_aesbool, optional (default: True)

If False, overrides the default aesthetics.

show_legendbool or dict, optional (default: None)

Whether this layer should be included in the legends. None the default, includes any aesthetics that are mapped. If a bool, False never includes and True always includes. A dict can be used to exclude specific aesthetis of the layer from showing in the legend. e.g show_legend={'color': False}, any other aesthetic are included by default.

rasterbool, optional (default: False)

If True, draw onto this layer a raster (bitmap) object even ifthe final image is in vector format.

directionstr, optional (default: hv)

One of hv, vh or mid, for horizontal-vertical steps, vertical-horizontal steps or steps half-way between adjacent x values.

See also


For documentation of extra parameters.


import pandas as pd
import numpy as np

from plotnine import (
from import economics

Step plots

geom_step() connects points using 'steps' instead of a line.

# inspect the data
date pce pop psavert uempmed unemploy
0 1967-07-01 507.4 198712 12.5 4.5 2944
1 1967-08-01 510.5 198911 12.5 4.7 2945
2 1967-09-01 516.3 199113 11.7 4.6 2958
3 1967-10-01 512.9 199311 12.5 4.9 3143
4 1967-11-01 518.1 199498 12.5 4.7 3066

Plot a step plot using geom_plot(). Notice from the first point the line travels vertically then horizontally:

    ggplot(economics.iloc[:20],                 # filter for first twenty rows (dates) to make steps more visible
           aes('date', 'unemploy'))
    + geom_step()                               # step plot
    + labs(x='date', y='unemployment (,000)')   # label x & y-axis
    + theme(axis_text_x=element_text(angle=45)) # rotate x-axis text for readability
<Figure Size: (640 x 480)>

You can see how geom_path() (shown in pink) differs from geom_line() (black):

           aes('date', 'unemploy'))
    + geom_step(colour='#ff69b4',              # plot geom_step as the first layer - colour pink
                alpha=0.5,                     # line transparency
                size=2.5)                      # line thickness
    + geom_line()                              # plot geom_line as the second layer
    + labs(x='date', y='unemployment (,000)')
    + theme(axis_text_x=element_text(angle=45))
<Figure Size: (640 x 480)>

Rather than a line that travels vertically then horizontally, this order can be switched by specifying direction='vh' within geom_step(). Below direction='vh' is shown in black with the default direction='hv' shown in pink:

           aes('date', 'unemploy'))
    + geom_step(colour='#ff69b4', # plot geom_path with default direction as the first layer - colour pink
                linetype='dashed',# line type
                size=2,           # line thickness
                alpha=0.5)        # line transparency
    + geom_step(direction='vh')   # plot geom_path with step order reversed
    + labs(x='date', y='unemployment (,000)')
    + theme(axis_text_x=element_text(angle=45))
<Figure Size: (640 x 480)>