28 publish map

Uncomment the following line to install leafmap if needed.

In [1]:

# !pip install leafmap

# !pip install leafmap

To follow this tutorial, you will need to sign up for an account with https://datapane.com, then install and authenticate the datapane Python package. More information can be found here.

• pip install datapane
• datapane login
• datapane ping

In [2]:

import leafmap.foliumap as leafmap

import leafmap.foliumap as leafmap

Create an elevation map of North America.

In [3]:

m = leafmap.Map()
m.add_basemap('USGS 3DEP Elevation')
colors = ['006633', 'E5FFCC', '662A00', 'D8D8D8', 'F5F5F5']
vmin = 0
vmax = 4000
m.add_colorbar(colors=colors, vmin=vmin, vmax=vmax)
m

m = leafmap.Map() m.add_basemap('USGS 3DEP Elevation') colors = ['006633', 'E5FFCC', '662A00', 'D8D8D8', 'F5F5F5'] vmin = 0 vmax = 4000 m.add_colorbar(colors=colors, vmin=vmin, vmax=vmax) m

Out[3]:

Make this Notebook Trusted to load map: File -> Trust Notebook

Publish the map to datapane.com

In [4]:

m.publish(name="Elevation Map of North America")

m.publish(name="Elevation Map of North America")

Connected successfully to https://datapane.com as giswqs

Bokeh version 2.4.2 is not supported, these plots may not display correctly, please install version ~=2.2.0

Uploading report and associated data - please wait...

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Create a land use and land cover map.

In [5]:

m = leafmap.Map()
m.add_basemap("NLCD 2016 CONUS Land Cover")
m.add_legend(builtin_legend='NLCD')
m

m = leafmap.Map() m.add_basemap("NLCD 2016 CONUS Land Cover") m.add_legend(builtin_legend='NLCD') m

Out[5]:

Make this Notebook Trusted to load map: File -> Trust Notebook

Publish the map to datapane.com.

In [6]:

m.publish(name="National Land Cover Database (NLCD) 2016")

m.publish(name="National Land Cover Database (NLCD) 2016")

Uploading report and associated data - please wait...

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Report successfully uploaded. View and share your report here, or edit your report here.

Create a world population heat map.

In [7]:

m = leafmap.Map()
in_csv = "https://raw.githubusercontent.com/giswqs/leafmap/master/examples/data/world_cities.csv"
m.add_heatmap(
    in_csv,
    latitude="latitude",
    longitude='longitude',
    value="pop_max",
    name="Heat map",
    radius=20,
)

m = leafmap.Map() in_csv = "https://raw.githubusercontent.com/giswqs/leafmap/master/examples/data/world_cities.csv" m.add_heatmap( in_csv, latitude="latitude", longitude='longitude', value="pop_max", name="Heat map", radius=20, )

In [8]:

colors = ['blue', 'lime', 'red']
vmin = 0
vmax = 10000
m.add_colorbar(colors=colors, vmin=vmin, vmax=vmax)
m

colors = ['blue', 'lime', 'red'] vmin = 0 vmax = 10000 m.add_colorbar(colors=colors, vmin=vmin, vmax=vmax) m

Out[8]:

Make this Notebook Trusted to load map: File -> Trust Notebook

Publish the map to datapane.com.

In [9]:

m.publish(name="World Population Heat Map")

m.publish(name="World Population Heat Map")

Uploading report and associated data - please wait...

Your report only contains a single element - did you know you can include additional plots, tables and text in a single report? More info here

Report successfully uploaded. View and share your report here, or edit your report here.

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Last update: 2022-03-14