Explain tile map with point on tile map and GeoJSON choropleth in plotly?
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Explain tile map with point on tile map and GeoJSON choropleth in plotly?

Explain tile map with point on tile map and GeoJSON choropleth in plotly?

This recipe explains what tile map with point on tile map and GeoJSON choropleth in plotly

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Recipe Objective

What are tile maps, Explain tile map with point on tile map and GeoJSON choropleths.

tile map these are the mapbox maps, if our figure is created with functions of plotly for e.g px.scatter_mapbox, px.line_mapbox, px.choropleth_mapbox or px.density_mapbox or on ther other side if it contains one or more traces of type go.Scattermapbox, go.Choroplethmapbox or go.Densitymapbox, the layout.mapbox object in your figure contains configuration information for the map itself.

GeoJSON choropleths these are the maps composed with of colored polygons, where it is used for representation of spactial variations of a quality. For choroleths map there are two steps to follow:

GeoJSON-Formatted geometry information where each feature has either an id field or some identifying value in properties.

A list of values indexed by feature identifier. In this the GeoJSON data is passed to the geojson argument, and the data is passed into the color argument of px.choloreths_mapbox as in the same order the ID's are passed in the location argument.

Step 1 - Import libraries

import plotly.express as px import seaborn as sns

Step 2 - load Dataset

Sample_data = px.data.carshare() Sample_data.head()

Step 3 - Plot graph

fig = px.scatter_mapbox(Sample_data, lat="centroid_lat", lon="centroid_lon", color="peak_hour", size="car_hours", color_continuous_scale=px.colors.cyclical.IceFire, size_max=15, zoom=10, mapbox_style="carto-positron") fig.show()

Here we have plotted the tile map with points on the tile in which we have used various functions which are required lets understand them:

lat - will define latitude for the map.

log - will definr longitutde for the map.

color - should be a column for defining the colors according to that column and data present in the dataset.

size - should be a column for defining the size according to that column and data present in the dataset.

color_continuos_scale - In this the data which will be string form should define valid CSS-colors. The list is used to build a continuous color scale when the column denoted by color contains numeric data.

size_max - It will set the maximum mark size when using size function the default is 20.

zoom - It will the int data between 0 and 20. Sets map zoom level. The default is 8.

mapbox_style - This will be string data by default it is 'basic', needs Mapbox API token. Identifier of base map style, some of which require a Mapbox API token to be set using plotly.express.set_mapbox_access_token(). Allowed values which do not require a Mapbox API token are 'open-street-map' 'white-bg', 'carto-positron', 'carto-darkmatter', 'stamen- terrain', 'stamen-toner', 'stamen-watercolor'. Allowed values which do require a Mapbox API token are 'basic', 'streets', 'outdoors', 'light', 'dark', 'satellite', 'satellite-streets'.

Step 4 - Plot the GeoJSON choropleths.

Sample_geo_data = px.data.election()##load the Sample data for geojson choropleths##load the Sample data for geojson choropleths

geojson_data = px.data.election_geojson() fig = px.choropleth_mapbox(Sample_geo_data, geojson=geojson_data, color="Bergeron", locations="district", featureidkey="properties.district", center={"lat": 45.5517, "lon": -73.7073}, mapbox_style="carto-positron", zoom=9) fig.show()

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