lets_plot.geom_bin2d

lets_plot.geom_bin2d(mapping=None, *, data=None, stat=None, position=None, show_legend=None, sampling=None, tooltips=None, bins=None, binwidth=None, drop=None, **other_args)

Display a 1d distribution by dividing variable mapped to x axis into bins and counting the number of observations in each bin.

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=’bin2d’

The statistical transformation to use on the data for this layer, as a string.

positionstr or FeatureSpec, default=’stack’

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.

binslist of int, default=[30, 30]

Number of bins in both directions, vertical and horizontal. Overridden by binwidth.

binwidthlist of float

The width of the bins in both directions, vertical and horizontal. Override bins. The default is to use bin widths that cover the entire range of the data.

dropbool, default=True

Specify whether to remove all bins with 0 counts.

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_bin2d() applies rectangular grid to the plane then counts observation in each cell of the grid (bin). Uses geom_tile() to display counts as a tile fill-color.

Computed variables:

• ..count.. : number of points with coordinates in the same bin.

geom_bin2d() understands the following aesthetics mappings:

• x : x-axis value.

• y : y-axis value.

• alpha : transparency level of a layer. Accept values between 0 and 1.

• color (colour) : color of the geometry lines. Can be continuous or discrete. For continuous value this will be a color gradient between two colors.

• fill : color of geometry filling, default: ‘..count..’. Alternatively: ‘..density..’.

• size : line width.

• weight : used by ‘bin’ stat to compute weighted sum instead of simple count.

Examples

import numpy as np
from lets_plot import *
LetsPlot.setup_html()
np.random.seed(42)
mean = np.zeros(2)
cov = np.eye(2)
x, y = np.random.multivariate_normal(mean, cov, 1000).T
ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + geom_bin2d()

import numpy as np
from lets_plot import *
LetsPlot.setup_html()
np.random.seed(42)
n = 5000
x = np.random.uniform(-2, 2, size=n)
y = np.random.normal(scale=.5, size=n)
ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + \
    geom_bin2d(aes(fill='..density..'), binwidth=[.25, .24], \
               tooltips=layer_tooltips().format('@x', '.2f')
                       .format('@y', '.2f').line('(@x, @y)')
                       .line('count|@..count..')
                       .format('@..density..', '.3f')
                       .line('density|@..density..')) + \
    scale_fill_gradient(low='black', high='red')

import numpy as np
from lets_plot import *
LetsPlot.setup_html()
np.random.seed(42)
mean = np.zeros(2)
cov = [[1, .5],
       [.5, 1]]
x, y = np.random.multivariate_normal(mean, cov, 500).T
ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + \
    geom_bin2d(aes(alpha='..count..'), bins=[20, 20], \
               color='white', fill='darkgreen') + \
    geom_point(size=1.5, shape=21, color='white', \
               fill='darkgreen') + \
    ggsize(600, 450)