Figure 6: GeoPandas

[yvonnefroehlich]

This PR adds a JN for GeoPandas - spatial data - GeoDataFrame:

• line geometry - pen parameter
• polygon geometry - cmap, aspatial parameters

[gitnotebooks]

Found 1 changed notebook. Review the changes at https://app.gitnotebooks.com/GenericMappingTools/pygmt-paper-figures/pull/6

[seisman]

I'm unsure if we need this example. As I understand it, PyGMT can plot GeoPandas objects, but its functionality for processing them is limited since the aspatial metadata will be lost during processing.

[yvonnefroehlich]

I'm unsure if we need this example. As I understand it, PyGMT can plot GeoPandas objects, but its functionality for processing them is limited since the aspatial metadata will be lost during processing.

I think the idea of having a choropleth map is, to show that there is functionality extending the feature available in GMT.

[seisman]

This example highlights GeoPandas integration in PyGMT. A geopandas.GeoDataFrame may contain any of the standard geometry types: Point, LineString, MultiLineString, Polygon, and MultiPolygon.

The script below plots three different datasets (available from https://www.naturalearthdata.com/) with different geometrie.

• world — country boundaries represented by Polygon and MultiPolygon geometries
• rivers — major rivers represented by LineString geometries
• cities — populated places represented by Point geometries

So, only MultiLineString is not covered.

import pygmt
import geopandas as gpd

world = gpd.read_file("https://naciscdn.org/naturalearth/50m/cultural/ne_50m_admin_0_countries.zip")
rivers = gpd.read_file("https://naciscdn.org/naturalearth/110m/physical/ne_110m_rivers_lake_centerlines.zip")  
cities = gpd.read_file("https://naciscdn.org/naturalearth/110m/cultural/ne_110m_populated_places_simple.zip")

world["POP_EST"] *= 1.0e-5

fig = pygmt.Figure()
fig.basemap(region="=SA", projection="M15c", frame=True)
fig.plot(data=world, pen="0.5p,black", fill="lightgreen")
pygmt.makecpt(cmap="turbo", series=(0, 3000, 100))
fig.plot(
    data=world,
    pen="0.2p,gray10",
    fill="+z",
    cmap=True,
    aspatial="Z=POP_EST",
)
fig.colorbar(frame=True)
fig.plot(data=rivers, pen="1p,blue")
fig.plot(data=cities, style="c0.1c", fill="red", pen="black")
fig.text(x=cities.geometry.x, y=cities.geometry.y, text=cities["name"], font="10p,Helvetica-Bold,black", offset="0.2c/0.2c")
fig.show()

[yvonnefroehlich]

Your example looks quite promising, but I get the following error when running the code:

UnicodeEncodeError: 'charmap' codec can't encode characters in position 0-7: character maps to
encoding with 'cp1252' codec failed

Will look it in detail tomorrow or within the next days.

[seisman]

It's likely because the city names contain non-ASCII characters, which doesn't work well in your console.

This is a likely solution for you:

cities["name"] = cities["name"].apply(lambda x: x.encode("utf-8", errors="ignore").decode("utf-8"))

[yvonnefroehlich]

It's likely because the city names contain non-ASCII characters, which doesn't work well in your console.

This is a likely solution for you:

cities["name"] = cities["name"].apply(lambda x: x.encode("utf-8", errors="ignore").decode("utf-8"))

Oh, thanks! I already tried something similar, but it did solve the problem yet. For now, I focus on the geometry column of the dataframe, then the codes work.

[yvonnefroehlich]

Using region="=SA" shows that country codes are supported. But the overlapping labels for the cities between 5°-25° North do not look nice.

region="SA"	region=[-89, -33, -56.5, 9.7]

[seisman]

Express the population in millions.

Suggested change

	world["POP_EST"] *= 1.0e-5
	world["POP_EST"] *= 1.0e-6

[seisman]

Suggested change

	pygmt.makecpt(cmap="batlow", series=(0, 2700, 100)) # 30000
	pygmt.makecpt(cmap="batlow", series=(0, 270, 10)) # 30000

[seisman]

Suggested change

	fig.colorbar(frame=["x+lPopulation", "y+l*10e-5"])
	fig.colorbar(frame=["x+lPopulation (millions)"])