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line and area on mapbox
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‎python/Line-on-Mapbox.md

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---
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jupyter:
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jupytext:
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notebook_metadata_filter: all
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text_representation:
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extension: .md
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format_name: markdown
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format_version: '1.1'
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jupytext_version: 1.2.1
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kernelspec:
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display_name: Python 3
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language: python
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name: python3
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language_info:
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codemirror_mode:
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name: ipython
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version: 3
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file_extension: .py
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mimetype: text/x-python
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name: python
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nbconvert_exporter: python
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pygments_lexer: ipython3
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version: 3.7.3
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plotly:
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description: How to make a Mapbox Choropleth Map of US Counties in Python with
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Plotly.
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display_as: maps
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has_thumbnail: true
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ipynb: ~notebook_demo/56
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language: python
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layout: user-guide
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name: Mapbox Choropleth Maps
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order: 1
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page_type: example_index
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permalink: python/mapbox-county-choropleth/
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thumbnail: thumbnail/mapbox-choropleth.png
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title: Python Mapbox Choropleth Maps | plotly
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---
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### Mapbox Access Token
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To plot on Mapbox maps with Plotly you *may* need a Mapbox account and a public [Mapbox Access Token](https://www.mapbox.com/studio). See our [Mapbox Map Layers](/python/mapbox-layers/) documentation for more information.
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### How to draw a Line on a Map
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To draw a line on your map, you either can use [Scattermapbox](https://plot.ly/python/reference/#scattermapbox) or [scattergeo](https://plot.ly/python/reference/#scattergeo) trace type. Then . In this example uses scattermapbox and define the drawing [mode](https://plot.ly/python/reference/#scattermapbox-mode) to the combination of markers and line.
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```python
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import plotly.graph_objects as go
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fig = go.Figure(go.Scattermapbox(
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mode = "markers+lines",
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lon = [10, 20, 30], lat = [10, 20,30],
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marker = {'size': 10}))
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fig.add_trace(go.Scattermapbox(
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mode = "markers+lines",
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lon = [-50, -60,40], lat = [30, 10, -20],
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marker = {'size': 10}))
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fig.update_layout(margin ={'l':0,'t':0,'b':0,'r':0},
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mapbox = {'center': {'lon': 10, 'lat': 10},
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'style': "stamen-terrain",
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'center': {'lon': -20, 'lat': -20},
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'zoom': 1})
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fig.show()
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```
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### Set Marker Symbols
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You can define a symbol on your map by setting [symbol](https://plot.ly/python/reference/#scattermapbox-marker-symbol) attribute. This attribute only works on mapbox tiles (not work on raster tiles):
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- basic
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- streets
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- outdoors
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- light
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- dark
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- satellite
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- satellite-streets
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```python
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import plotly.graph_objects as go
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token = open(".mapbox_token").read() # you need your own token
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fig = go.Figure(go.Scattermapbox(
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mode = "markers+text+lines",
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lon = [-75, -80, -50], lat = [45, 20, -20],
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marker = {'size': 20, 'symbol': ["bus", "harbor", "airport"]},
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text = ["Bus", "Harbor", "airport"],textposition = "bottom right"))
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fig.update_layout(
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mapbox = {
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'accesstoken': token,
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'style': "outdoors", 'zoom': 0.7},
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showlegend = False)
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fig.show()
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```
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### Contour Line on Glob
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This example uses [scattergeo](https://plot.ly/javascript/reference/#scattergeo) trace type to visualize the data as lines on a geographic map.
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```python
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import plotly.graph_objects as go
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import pandas as pd
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df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/globe_contours.csv')
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scl = ['blue', 'yellow', 'pink', \
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'royalblue', 'fuchsia', 'blue', \
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'brown', 'purple', 'orange']
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n_colors = len(scl)
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fig = go.Figure()
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for i, (lat, lon) in enumerate(zip(df.columns[::2], df.columns[1::2])):
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fig.add_trace(go.Scattergeo(
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lon = df[lon],
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lat = df[lat],
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mode = 'lines',
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line = dict(width = 2, color = scl[i % n_colors]
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)))
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fig.update_layout(
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title_text = 'Contour lines over globe<br>(Click and drag to rotate)',
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showlegend = False,
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geo = dict(
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showland = True,
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showcountries = True,
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showocean = True,
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countrywidth = 0.5,
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landcolor = 'orange',
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lakecolor = 'cyan',
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oceancolor = 'cyan',
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projection = dict(
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type = 'orthographic',
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rotation = dict(
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lon = -100,
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lat = 40,
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roll = 0
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)
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),
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lonaxis = dict(
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showgrid = True,
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gridcolor = 'black',
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gridwidth = 0.5
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),
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lataxis = dict(
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showgrid = True,
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gridcolor = 'black',
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gridwidth = 0.5
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)
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)
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)
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fig.show()
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```
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#### Reference
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See https://plot.ly/python/reference/#choroplethmapbox for more information about mapbox and their attribute options.

‎python/Mapbox-area.md

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---
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jupyter:
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jupytext:
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notebook_metadata_filter: all
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text_representation:
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extension: .md
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format_name: markdown
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format_version: '1.1'
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jupytext_version: 1.2.1
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kernelspec:
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display_name: Python 3
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language: python
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name: python3
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language_info:
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codemirror_mode:
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name: ipython
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version: 3
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file_extension: .py
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mimetype: text/x-python
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name: python
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nbconvert_exporter: python
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pygments_lexer: ipython3
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version: 3.7.3
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plotly:
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description: How to make a Mapbox Choropleth Map of US Counties in Python with
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Plotly.
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display_as: maps
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has_thumbnail: true
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ipynb: ~notebook_demo/56
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language: python
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layout: user-guide
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name: Mapbox Choropleth Maps
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order: 1
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page_type: example_index
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permalink: python/mapbox-county-choropleth/
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thumbnail: thumbnail/mapbox-choropleth.png
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title: Python Mapbox Choropleth Maps | plotly
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---
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### Mapbox Access Token
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To plot on Mapbox maps with Plotly you *may* need a Mapbox account and a public [Mapbox Access Token](https://www.mapbox.com/studio). See our [Mapbox Map Layers](/python/mapbox-layers/) documentation for more information.
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### How to Show an Area on a Map
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There are three different ways to show an area in a mapbox:
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- Set `fill` attribute to 'toself'
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- Define the corresponding geojson
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- Use the new trace type: [Choroplethmapbox](https://plot.ly/python/mapbox-county-choropleth/) for mapbox cases, or [Choropleth](https://plot.ly/python/choropleth-maps/) trace for non-mapbox ones.
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The following example uses `Scattermapbox` and sets `fill = 'toself'`
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```python
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import plotly.graph_objects as go
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fig = go.Figure(go.Scattermapbox(
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fill = "toself",
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lon = [-74, -70, -70, -74], lat = [47, 47, 45, 45],
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marker = { 'size': 10, 'color': "orange" }))
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fig.update_layout(
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mapbox = {
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'style': "stamen-terrain",
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'center': {'lon': -73, 'lat': 46 },
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'zoom': 5},
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showlegend = False)
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fig.show()
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```
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### Provide Gaps on Map
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The following example shows how to use missing values in your data to provide gap in your graph. To ignore the gap on your plot, take benefit of [connectorgaps](https://plot.ly/python/reference/#scattermapbox-connectgaps) attribute.
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```python
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import plotly.graph_objects as go
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fig = go.Figure(go.Scattermapbox(
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mode = "lines", fill = "toself",
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lon = [-10, -10, 8, 8, None, 30, 30, 50, 50, None, 100, 100, 80, 80], lat = [30, 6, 6, 30, None, 20, 30, 30, 20, None, 40, 50, 50, 40]))
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fig.update_layout(
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mapbox = {'style': "stamen-terrain", 'center': {'lon': 30, 'lat': 30}, 'zoom': 2},
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showlegend = False,
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margin = {'l':0, 'r':0, 'b':0, 't':0})
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fig.show()
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```
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### Use the Coresponding Geojson
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```python
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import plotly.graph_objects as go
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fig = go.Figure(go.Scattermapbox(
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mode = "markers",
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lon = [-73.605], lat = [45.51],
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marker = {'size': 20, 'color': ["cyan"]}))
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fig.update_layout(
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mapbox = {
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'style': "stamen-terrain",
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'center': { 'lon': -73.6, 'lat': 45.5},
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'zoom': 12, 'layers': [{
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'source': {
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'type': "FeatureCollection",
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'features': [{
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'type': "Feature",
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'geometry': {
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'type': "MultiPolygon",
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'coordinates': [[[
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[-73.606352888, 45.507489991], [-73.606133883, 45.50687600],
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[-73.605905904, 45.506773980], [-73.603533905, 45.505698946],
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[-73.602475870, 45.506856969], [-73.600031904, 45.505696003],
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[-73.599379992, 45.505389066], [-73.599119902, 45.505632008],
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[-73.598896977, 45.505514039], [-73.598783894, 45.505617001],
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[-73.591308727, 45.516246185], [-73.591380782, 45.516280145],
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[-73.596778656, 45.518690062], [-73.602796770, 45.521348046],
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[-73.612239983, 45.525564037], [-73.612422919, 45.525642061],
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[-73.617229085, 45.527751983], [-73.617279234, 45.527774160],
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[-73.617304713, 45.527741334], [-73.617492052, 45.527498362],
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[-73.617533258, 45.527512253], [-73.618074188, 45.526759105],
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[-73.618271651, 45.526500673], [-73.618446320, 45.526287943],
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[-73.618968507, 45.525698560], [-73.619388002, 45.525216750],
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[-73.619532966, 45.525064183], [-73.619686662, 45.524889290],
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[-73.619787038, 45.524770086], [-73.619925742, 45.524584939],
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[-73.619954486, 45.524557690], [-73.620122362, 45.524377961],
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[-73.620201713, 45.524298907], [-73.620775593, 45.523650879]
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]]]
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}
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}]
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},
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'type': "fill", 'below': "traces", 'color': "royalblue"}]},
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margin = {'l':0, 'r':0, 'b':0, 't':0})
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fig.show()
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```
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#### Reference
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See https://plot.ly/python/reference/#choroplethmapbox for more information about mapbox and their attribute options.

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