hvPlot.hexbin#
- hvPlot.hexbin(x=None, y=None, C=None, colorbar=True, gridsize=50, logz=False, min_count=None, **kwds)[source]#
The hexbin plot uses hexagons to split the area into several parts and attribute a color to it.
hexbin offers a straightforward method for plotting dense data.
Reference: https://hvplot.holoviz.org/reference/tabular/hexbin.html
- Parameters:
- xstring, optional
Field name to draw x coordinates from. If not specified, the index is used.
- ystring
Field name to draw y-positions from
- Cstring, optional
Field to draw hexbin color from. If not specified a simple count will be used.
- colorbar: boolean, optional
Whether to display a colorbar. Default is True.
- reduce_functionfunction, optional
Function to compute statistics for hexbins, for example np.mean. Default aggregation is a count of the values in the area.
- gridsize: int or tuple, optional
Number of hexagonal bins along x- and y-axes. Defaults to uniform sampling along both axes when setting and integer but independent bin sampling can be specified a tuple of integers corresponding to the number of bins along each axis. Default is 50.
- logzbool
Whether to apply log scaling to the z-axis. Default is False.
- min_countnumber, optional
The display threshold before a bin is shown, by default bins with a count of less than 1 are hidden
- **kwdsoptional
Additional keywords arguments are documented in hvplot.help(‘hexbin’). See Plotting Options for more information.
- Returns:
holoviews.element.HexTiles
/ Panel objectYou can print the object to study its composition and run:
import holoviews as hv hv.help(the_holoviews_object)
to learn more about its parameters and options.
References
Bokeh: https://docs.bokeh.org/en/latest/docs/gallery/hexbin.html
HoloViews: https://holoviews.org/reference/elements/bokeh/HexTiles.html
Wiki: https://think.design/services/data-visualization-data-design/hexbin/
Examples
import hvplot.pandas import pandas as pd import numpy as np n = 500 df = pd.DataFrame({ "x": 2 + 2 * np.random.standard_normal(n), "y": 2 + 2 * np.random.standard_normal(n), }) df.hvplot.hexbin("x", "y", clabel="Count", cmap="plasma_r", height=400, width=500)
Backend-specific styling options#
alpha, cmap, color, fill_alpha, fill_color, hover_alpha, hover_color, hover_fill_alpha, hover_fill_color, hover_line_alpha, hover_line_cap, hover_line_color, hover_line_dash, hover_line_dash_offset, hover_line_join, hover_line_width, line_alpha, line_cap, line_color, line_dash, line_dash_offset, line_join, line_width, muted, muted_alpha, muted_color, muted_fill_alpha, muted_fill_color, muted_line_alpha, muted_line_cap, muted_line_color, muted_line_dash, muted_line_dash_offset, muted_line_join, muted_line_width, nonselection_alpha, nonselection_color, nonselection_fill_alpha, nonselection_fill_color, nonselection_line_alpha, nonselection_line_cap, nonselection_line_color, nonselection_line_dash, nonselection_line_dash_offset, nonselection_line_join, nonselection_line_width, scale, selection_alpha, selection_color, selection_fill_alpha, selection_fill_color, selection_line_alpha, selection_line_cap, selection_line_color, selection_line_dash, selection_line_dash_offset, selection_line_join, selection_line_width, visible
alpha, cmap, ec, edgecolor, edgecolors, linewidths, marginals
Examples#
TBD