Plotly.py: Figure factory: Plot a scalar field with geographical coordinates on map with projection

[ghost]

I have an array of global temperatures and associated longitude and latitude coordinates arrays. I would like to plot the temperatures as a heatmap on a map with custom projection and showing coastlines.
A working code example using matplotlib is:

import matplotlib.pyplot as plt
import cartopy.crs as ccrs

f, ax = plt.subplots(subplot_kw={'projection': ccrs.Robinson()})
p = ax.pcolormesh(longitude, latitude, temperature, cmap='RdBu_r', transform=ccrs.PlateCarree())
ax.coastlines()
f.colorbar(p, orientation='horizontal')

The output figure from code block above is (data available here):

At the moment I was only able to use plotly for a simple heatmap with the following code:

from plotly.offline import iplot
import plotly.graph_objs as go

layout = go.Layout(geo={'projection': {'type': 'robinson'}})
data = go.Heatmap(x=longitude, y=latitude, z=temperature)

fig = go.Figure(data=[data], layout=layout)
iplot(fig)

As next figure shows, main issues are:

• the projection is not working;

• no coastlines are shown.
  

[Balinus]

Would also love something similar!

[empet]

You can plot both heatmap and contour plots on maps. Take a look here: https://plot.ly/~Dreamshot/9147 or visit this user (Dreamshot) Plotly profile for more examples.

[Balinus]

Thanks! Will take a look :)

[Balinus]

Although it does not seem to support mapping per se. I mean, the data are on a lat-lon coordinates, but what if we want to change the projection? I don't see a proper support for maps right out of the box (or at least without creating a unique map for each use case).

[JiaweiZhuang]

This blog should help: How to Create 2D and 3D Interactive Weather Maps in Python and R

[jonmmease]

A geographic heatmap figure factory would be really nice!