gdf2bokeh 2.3.2

An easy way to map geodataframes on bokeh

gdf2bokeh

An easy way to map your geographic data (from a GeoDataFrame) with bokeh >=2.3 Because it's boring to convert shapely geometry to bokeh format !!

How to install the conda package ?

With Anaconda

conda install -c amauryval gdf2bokeh

with pip

pip install gdf2bokeh

How to use it ?!

A small example :

Check bokeh documentation in order to style your data :

• bokeh marker style options to style point features
• bokeh multi_line style options to style LineString and MultiLineString features
• bokeh multi_polygon style options to style polygon and multipolygons features

from bokeh.plotting import show
import geopandas as gpd
from gdf2bokeh import Gdf2Bokeh

layers_to_add = [
    {
        "input_gdf": gpd.GeoDataFrame.from_file("your_geo_layer.geojson"),
        "legend": "My beautiful layer",  # required, can be the name of an column name (from your input gdf)
        "fill_color": "orange",  # here we found one argument use by bokeh to style your layer. Take care about geometry type
    },
    {
        "input_wkt": "LINESTRING(0 0, 25 25)",  # you can add an input wkt
        "legend": "My beautiful layer",  # required
        "color": "orange",  # here we found one argument use by bokeh to style your layer. Take care about geometry type
    }
]
# Points, LineString, MultiLineString, Polygons (+ holes) and MultiPolygons (+ holes) are supported

my_map = Gdf2Bokeh(
    "My beautiful map",  # required: map title
    width=800,  # optional: figure width, default 800
    height=600,  # optional: figure width, default 600
    x_range=None,  # optional: x_range, default None
    y_range=None,  # optional: y_range, default None
    background_map_name="CARTODBPOSITRON",  # optional: background map name, default: CARTODBPOSITRON
    layers=layers_to_add    # optional: bokeh layer to add from a list of dict contains geodataframe settings, see dict above
)
# to get all the bokeh layer containers (dict), in order to update them (interactivity, slider... on a bokeh serve)
bokeh_layer_containers = my_map.get_bokeh_layer_containers

show(my_map.figure)

Also, you can find a bokeh serve example with a slider widget. On the terminal, run :

bokeh serve --show bokeh_serve_example.py