plotnine.geom_linerange

geom_linerange(
    mapping=None,
    data=None,
    *,
    stat="identity",
    position="identity",
    na_rm=False,
    inherit_aes=True,
    show_legend=None,
    raster=False,
    **kwargs
)

Vertical interval represented by lines

Parameters

mapping : aes = None

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.

Aesthetic	Default value
x
ymax
ymin
alpha	1
color	'black'
group
linetype	'solid'
size	0.5

The bold aesthetics are required.

data : DataFrame = None

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.

stat : str | 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.

position : str | position = "identity"

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

na_rm : bool = False

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

inherit_aes : bool = True

If False, overrides the default aesthetics.

show_legend : bool | dict = 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.

raster : bool = False

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

**kwargs : Any = {}

Aesthetics or parameters used by the stat.

Examples

import pandas as pd
from plotnine import (
    ggplot,
    aes,
    geom_point,
    geom_line,
    geom_linerange,
    element_blank,
    element_rect,
    theme,
    theme_matplotlib,
    theme_set,
)

# Set default theme
# matplotlib + the background of 538
theme_set(
    theme_matplotlib()
    + theme(
        plot_background=element_rect(fill="#F0F0F0"),
        panel_background=element_rect(fill="#F0F0F0"),
    )
)

Upper & Lower Trends

The data

df = pd.DataFrame({
    "x": range(0, 6),
    "y": [3, 4, 3.5, 4.5, 4, 4]
})

Create the line ranges

(ggplot(df, aes("x", "y"))
 + geom_linerange(aes(ymin="y-2", ymax="y"))
)

Add points at each end of the ranges.

(ggplot(df, aes("x", "y"))
 + geom_linerange(aes(ymin="y-2", ymax="y"))
 + geom_point()
 + geom_point(aes(y="y-2"))

)

Add a trend-line along the top of the ranges and one along the bottom of the ranges. The line is added before(below) the points.

(ggplot(df, aes("x", "y"))
 + geom_linerange(aes(ymin="y-2", ymax="y"))
 
 + geom_line()
 + geom_point()

 + geom_line(aes(y="y-2"))
 + geom_point(aes(y="y-2"))

)

Add some color.

# Gallery, lines
magenta = "#9E2F68"
magenta_light = "#E5C8D6"

sea_green = "#2F9E65"
sea_green_light = "#C8E5D7"

(ggplot(df, aes("x", "y"))
 + geom_linerange(aes(ymin="y-2", ymax="y"))
 
 + geom_line(color=magenta, size=3)
 + geom_point(color=magenta, fill=magenta_light, size=3, stroke=0.5)
 
 + geom_line(aes(y="y-2"), color=sea_green, size=3)
 + geom_point(aes(y="y-2"), color=sea_green, fill=sea_green_light, size=3, stroke=0.5)
)

Source: Set default theme