lets_plot.geom_pointrange¶
- lets_plot.geom_pointrange(mapping=None, *, data=None, stat=None, position=None, show_legend=None, sampling=None, tooltips=None, fatten=None, color_by=None, fill_by=None, **other_args)¶
Add a vertical line defined by upper and lower value with midpoint at y location.
- Parameters
- mappingFeatureSpec
Set of aesthetic mappings created by aes() function. Aesthetic mappings describe the way that variables in the data are mapped to plot “aesthetics”.
- datadict or DataFrame or polars.DataFrame
The data to be displayed in this layer. If None, the default, the data is inherited from the plot data as specified in the call to ggplot.
- statstr, default=’identity’
The statistical transformation to use on the data for this layer, as a string. Supported transformations: ‘identity’ (leaves the data unchanged), ‘count’ (counts number of points with same x-axis coordinate), ‘bin’ (counts number of points with x-axis coordinate in the same bin), ‘smooth’ (performs smoothing - linear default), ‘density’ (computes and draws kernel density estimate).
- positionstr or FeatureSpec, default=’identity’
Position adjustment, either as a string (‘identity’, ‘stack’, ‘dodge’, …), or the result of a call to a position adjustment function.
- show_legendbool, default=True
False - do not show legend for this layer.
- samplingFeatureSpec
Result of the call to the sampling_xxx() function. To prevent any sampling for this layer pass value “none” (string “none”).
- tooltipslayer_tooltips
Result of the call to the layer_tooltips() function. Specify appearance, style and content.
- fattenfloat, default=5.0
A multiplicative factor applied to size of the middle point.
- color_by{‘fill’, ‘color’, ‘paint_a’, ‘paint_b’, ‘paint_c’}, default=’color’
Define the color aesthetic for the geometry.
- fill_by{‘fill’, ‘color’, ‘paint_a’, ‘paint_b’, ‘paint_c’}, default=’fill’
Define the fill aesthetic for the geometry.
- other_args
Other arguments passed on to the layer. These are often aesthetics settings used to set an aesthetic to a fixed value, like color=’red’, fill=’blue’, size=3 or shape=21. They may also be parameters to the paired geom/stat.
- Returns
- LayerSpec
Geom object specification.
Notes
geom_pointrange() represents a vertical interval, defined by x, ymin, ymax. The mid-point is defined by y.
geom_pointrange() understands the following aesthetics mappings:
x : x-axis coordinates.
y : position of mid-point.
ymin : lower bound for error bar.
ymax : upper bound for error bar.
alpha : transparency level of a layer. Accept values between 0 and 1.
color (colour) : color of the geometry lines. String in the following formats: RGB/RGBA (e.g. “rgb(0, 0, 255)”); HEX (e.g. “#0000FF”); color name (e.g. “red”).
fill : fill color. String in the following formats: RGB/RGBA (e.g. “rgb(0, 0, 255)”); HEX (e.g. “#0000FF”); color name (e.g. “red”).
size : line width, size of mid-point.
linetype : type of the line. Codes and names: 0 = ‘blank’, 1 = ‘solid’, 2 = ‘dashed’, 3 = ‘dotted’, 4 = ‘dotdash’, 5 = ‘longdash’, 6 = ‘twodash’.
shape : shape of the mid-point, an integer from 0 to 25.
stroke : width of the shape border. Applied only to the shapes having border.
Examples
1from lets_plot import * 2LetsPlot.setup_html() 3data = { 4 'x': ['a', 'b', 'c', 'd'], 5 'ymin': [5, 7, 3, 5], 6 'y': [6.5, 9, 4.5, 7], 7 'ymax': [8, 11, 6, 9], 8} 9ggplot(data, aes(x='x', y='y')) + \ 10 geom_pointrange(aes(ymin='ymin', ymax='ymax'))
1import numpy as np 2import pandas as pd 3from lets_plot import * 4LetsPlot.setup_html() 5n = 800 6cat_list = {c: np.random.uniform(3) for c in 'abcdefgh'} 7np.random.seed(42) 8x = np.random.choice(list(cat_list.keys()), n) 9y = np.array([cat_list[c] for c in x]) + np.random.normal(size=n) 10df = pd.DataFrame({'x': x, 'y': y}) 11err_df = df.groupby('x').agg({'y': ['min', 'mean', 'max']}).reset_index() 12err_df.columns = ['x', 'ymin', 'ymean', 'ymax'] 13ggplot(err_df, aes(x='x', y='ymean')) + \ 14 geom_pointrange(aes(ymin='ymin', ymax='ymax'), \ 15 show_legend=False, fatten=10, shape=4, \ 16 color='red', size=1)