Deckgl Charts

Choropleth Chart

deckgl.choropleth(color_column, elevation_column=None, color_aggregate_fn='count', color_factor=1, elevation_aggregate_fn='sum', elevation_factor=1, add_interaction=True, width=800, height=400, geoJSONSource=None, geoJSONProperty=None, geo_color_palette=None, mapbox_api_key=None, map_style=None, tooltip=True, tooltip_include_cols=[], nan_color='#d3d3d3', **library_specific_params)

Parameters:

x: str

x-axis column name from the gpu dataframe

color_column: str

column name from the gpu dataframe on which color palettes are based on

elevation_column: str | Optional

column name from the gpu dataframe on which elevation scale is based on

color_aggregate_fn: {‘count’, ‘mean’, ‘sum’, ‘min’, ‘max’, ‘std’},

default “count”

aggregate function to be applied on the color column while performing groupby aggregation by column x

color_factor: float, default 1

factor to be multiplied to each value of color column before mapping the color

elevation_aggregate_fn: {‘count’, ‘mean’, ‘sum’, ‘min’, ‘max’, ‘std’},

default “count”

aggregate function to be applied on the elevation column while performing groupby aggregation by column x

elevation_factor: float, default 1

factor to be multiplied to each value of elevation column before scaling the elevation

add_interaction: {True, False}, default True

width: int, default 800

height: int, default 400

geoJSONSource: str

url to the geoJSON file

geoJSONProperty: str, optional

Property to use while doing aggregation operations using the geoJSON file. Defaults to the first value in properties in geoJSON file.

geo_color_palette: bokeh.palette, default bokeh.palettes.Inferno256

mapbox_api_key: str, default os.getenv(‘MAPBOX_API_KEY’)

map_style: str,

default based on cuxfilter.themes:

dark/rapids theme: ‘mapbox://styles/mapbox/dark-v9’ light theme: ‘mapbox://styles/mapbox/light-v9’

URI for Mapbox basemap style. See Mapbox’s https://docs.mapbox.com/mapbox-gl-js/example/setstyle/ for examples

tooltip: {True, False}, default True

tooltip_include_cols: [], default list(dataframe.columns)

nan_color: hex color code, default cuxfilter.charts.CUXF_NAN_COLOR

color of the patches of value NaN in the map.

title: str,

chart title

**library_specific_params:

additional library specific keyword arguments to be passed to the function

Returns:

A bokeh chart object of type 3dchoropleth

Example 3d-Choropleth

import numpy as np
import cudf
import cuxfilter

geoJSONSource='https://raw.githubusercontent.com/rapidsai/cuxfilter/GTC-2018-mortgage-visualization/javascript/demos/GTC%20demo/src/data/zip3-ms-rhs-lessprops.json'
size = 1000

cux_df = cuxfilter.DataFrame.from_dataframe(
    cudf.DataFrame({
                    'color':np.random.randint(20,30, size=size*10)/100,
                    'zip': list(np.arange(1,1001))*10,
                    'elevation': np.random.randint(0,1000, size=size*10)
    })
)

chart0 = cuxfilter.charts.choropleth( x='zip', color_column='color', color_aggregate_fn='mean',
            elevation_column='elevation', elevation_factor=1000, elevation_aggregate_fn='mean',
        geoJSONSource=geoJSONSource, data_points=size, add_interaction=True
)

#declare dashboard
d = cux_df.dashboard([chart0],theme = cuxfilter.themes.dark, title='Mortgage Dashboard')

# use chart0.view() in a notebook cell to view the individual charts
chart0.view()