/notebook_gis_plotting

Plotting examples of geospatial data in Jupyter notebooks

Primary LanguageJupyter NotebookMIT LicenseMIT

A comparison of several plotting techniques for Jupyter Notebooks.

if you miss a repo please PR.

Geopandas

Pros:

  1. Simple.
  2. No API keys required.

Cons:

  1. Static.
  2. No tooltip.

Folium

Pros:

  1. Open Source
  2. Fair inter operability with geopandas.
  3. Customizable.

Cons:

  1. Data is all client side.
  2. No vector tiles.
  3. Fails with larger datasets.

MapboxGL for Jupyter

Pros:

  1. Vector tiles.
  2. 3D.
  3. WebGL power.
  4. Useful tools to generate colormaps.
  5. use client side data for choropleth maps.

Cons:

  1. API key required
  2. Choropleth maps created with join method have a limited tooltip.
  3. Need to convert data into JSON.
  4. No layered approach (yet).

Cartoframes

Pros:

  1. Vector tiles.
  2. Querable.
  3. Choropleth and tooltips supported.
  4. Can handle server side and client side data layers.

Cons:

  1. In alpha stage.
  2. 2D only.
  3. How to combine server and client side data in one map.

Other

  1. cartopy. Good for printing static maps.
  2. ... please add PR.