带标签的Geopandas图

Question

I have a geopandas file:

from shapely.geometry import Point, LineString
import geopandas

line1 = LineString([
    Point(0, 0),
    Point(0, 1),
    Point(1, 1),
    Point(1, 2),
    Point(3, 3),
    Point(5, 6),
])

line2 = LineString([
    Point(5, 3),
    Point(5, 5),
    Point(9, 5),
    Point(10, 7),
    Point(11, 8),
    Point(12, 12),
])

line3 = LineString([
    Point(9, 10),
    Point(10, 14),
    Point(11, 12),
    Point(12, 15),
])

gdf = geopandas.GeoDataFrame(
    data={'name': ['A', 'B', 'A']},
    geometry=[line1, line2, line3]
)

Now, I would like to plot it, but depending on the name "A", "B" ist should either be plotted in red or in black. My real dataset is much much larger. Therefore, a efficient solution would be highly appreciated. Thanks!

Answer 1

You could add a column with a numeric equivalent and define your own cmap. You can use 0 and 1 for A and B or 0, 0.5 and 1 for A, B and C and so on.

from shapely.geometry import Point, LineString
import geopandas
from matplotlib.colors import LinearSegmentedColormap
from matplotlib import pyplot as plt


line1 = LineString([
    Point(0, 0), Point(0, 1), Point(1, 1), Point(1, 2),
    Point(3, 3), Point(5, 6),])

line2 = LineString([
    Point(5, 3), Point(5, 5), Point(9, 5), Point(10, 7),
    Point(11, 8), Point(12, 12),])

line3 = LineString([
    Point(9, 10), Point(10, 14), Point(11, 12), Point(12, 15),])

gdf = geopandas.GeoDataFrame(
    data={'name': ['A', 'B', 'A']},
    geometry=[line1, line2, line3]
)

my_cmap = LinearSegmentedColormap.from_list(
    'mycmap', [(0, 'red'), (1, '#000000')])

gdf['num'] = gdf['name'].replace({'A': 0, 'B': 1})

gdf.plot(cmap=my_cmap, column='num')
plt.show()