create legend for markercolor and size - matplotlib

Question

I've created the following figure:
With following code:
matplotlib.rcParams.update({'font.size': 10})
fig = plt.figure(figsize=(16, 9), dpi=300, facecolor='white')
ax = plt.subplot(111, projection=ccrs.PlateCarree())
ax.set_extent(extent)
# cartopy layers
country_10m = cartopy.feature.NaturalEarthFeature('cultural', 'admin_0_countries', '10m')
ax.add_feature(country_10m, edgecolor='w', linewidth=0.75, facecolor='#EEEFEE', label='country border')
ax.coastlines(resolution='10m', color='#EEEFEE', linewidth=0.75)
ax.imshow(np.tile(np.array([[[191, 210, 217]]], dtype=np.uint8), [2, 2, 1]), origin='lower', transform=cartopy.crs.PlateCarree(), extent=extent)
ax.scatter(gdf_ldb.x, gdf_ldb.y, c= gdf_ldb.Color, s= gdf_ldb.Markersize, zorder=30)
# ax.scatter(gdf_ports_filt.longitude, gdf_ports_filt.latitude, s= 10, color= 'k', zorder= 30)
ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=True, linewidth=1, color='gray', alpha=0.5, linestyle='-')
ax.text(-0.08, 0.5, 'latitude [°]', va='bottom', ha='center',rotation='vertical', rotation_mode='anchor',transform=ax.transAxes);
ax.text(0.5, -0.09, 'longitude [°]', va='bottom', ha='center', rotation='horizontal', rotation_mode='anchor', transform=ax.transAxes);
How do I create a legend for the markersize as well for the color, so like this:
With x, x1, and x2 representing the values of the markersizes.
gdf_ldb looks like:
x y Type Color Markersize geometry
prograding_feature_polygon_29 12.857701 56.648035 Updrift grey 3.0 POINT (12.85770 56.64804)
prograding_feature_polygon_57 17.781445 54.808079 Updrift grey 3.0 POINT (17.78144 54.80808)
prograding_feature_polygon_58 17.438390 54.754518 Updrift grey 3.0 POINT (17.43839 54.75452)
prograding_feature_polygon_63 4.708077 52.880322 Updrift grey 3.0 POINT (4.70808 52.88032)
prograding_feature_polygon_72 3.953364 51.842299 Updrift grey 3.0 POINT (3.95336 51.84230)
... ... ... ... ... ... ...
retreating_feature_polygon_2018 -10.148432 53.415224 Double Updrift grey 3.0 POINT (-10.14843 53.41522)
retreating_feature_polygon_2019 -9.954510 54.197329 Double Updrift grey 3.0 POINT (-9.95451 54.19733)
retreating_feature_polygon_2119 15.095564 37.389535 Double Updrift grey 3.0 POINT (15.09556 37.38953)
retreating_feature_polygon_2120 14.317893 37.025026 Double Updrift grey 3.0 POINT (14.31789 37.02503)
retreating_feature_polygon_2121 13.952111 37.101009 Updrift grey 3.0 POINT (13.95211 37.10101)
Thanks in advance,
Dante

Answer 1

The key is to capture the artist (PathCollection in this case) returned by the scatter command. That has a method to retrieve the legend items manually, and it has keywords to distinguish between size and color (default). The num keyword can be used to reduce the amount of items returned, which is useful in the case of a (semi)continuous property as the size can be.
The example below plots two separate legends for both properties. You can also combine the handles and labels of both and plot them in a single legend if needed.
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import cartopy.crs as ccrs
import cartopy
import numpy as np
lons = np.random.randint(-170, 170, 100)
lats = np.random.randint(-80, 80, 100)
sizes = np.random.rand(100) * 100 + 5
colors = np.random.randint(0, 3, 100)
fig, ax = plt.subplots(
figsize=(8,4), dpi=86, facecolor='w',
subplot_kw=dict(projection=ccrs.PlateCarree()),
)
fig.subplots_adjust(left=0, right=1, bottom=0, top=1)
ax.add_feature(cartopy.feature.LAND, ec='none', fc='#EEEFEE', label='country border')
ax.add_feature(cartopy.feature.BORDERS, ec='w', fc='k', lw=0.75, label='country border')
ax.coastlines(resolution='10m', color='#EEEFEE', lw=0.75)
m = ax.scatter(lons, lats, s=sizes, c=colors, zorder=5, label="points")
l1 = ax.legend(
*m.legend_elements(prop="colors", num="auto"), title="Colors", framealpha=1,
loc="upper right", bbox_to_anchor=(0.88, 0.8, 0.12, 0.2), mode="expand",
)
ax.add_artist(l1) # prevent overwriting with second legend
l2 = ax.legend(
*m.legend_elements(prop="sizes", num=5), title="Sizes", framealpha=1,
loc="upper right", bbox_to_anchor=(0.88, 0.55, 0.12, 0.2), mode="expand",
)
The documentation about this shows some variations on this:
https://matplotlib.org/stable/gallery/lines_bars_and_markers/scatter_with_legend.html#automated-legend-creation

Answer 2

The answer by Rutger Kassies is excellent for many use cases. However, he mentions that One can also combine the handles and labels of both and plot them in a single legend if needed.
Here I offer another answer that shows the steps to create the single legend manually. Inside the single legend, 2 groups of sub legends are created and arranged as needed.
With single legend, you don't need to find the values of bbox_to_anchor for the second (or third and so on) to position them properly.
With manual creation of items into a single legend, you have full control of the items' you need in the legend. However, it need some extra coding to achieve the goal.
import matplotlib.pyplot as plt
import matplotlib.lines as mlines
import cartopy.crs as ccrs
import cartopy.feature as cfeature
# For `Categories` symbol
# Each item of legends requires 3 properties: color/text/marker_shape
color_V = ["green", "orange", "purple", "red", "cyan", "magenta"]
text_V = ["cat_4", "cat_9", "cat_13", "cat_15", "cat_19", "cat_33"]
marker_V = ["o", "o", "o", "o", "o", "o"]
len_V = len(color_V)
# For `Size/values` symbol
color_S = ["gray", "gray", "gray", "gray"]
sizes_S = [4, 8, 12, 16] #increasing values ...
text_S = ["4", "8", "12", "16"] #cover `sizes1` below
marker_S = ["o", "o", "o", "o"] #use disk shape
len_S = len(color_S)
# Demo data locations and attributes
xs = [23,12,4,25,24,52,17,33]
ys = [41,12,32,15,35,21,23,43]
colors1 = ["green", "orange", "purple", "red", "cyan", "magenta", "green", "orange"]
#texts1 = ["4", "9", "13", "15", "19", "33", "4", "9"]
markers1 = ["o", "o", "o", "o", "o", "o", "o", "o"]
sizes1 = [10,16,9,12,7,4,2,6]
len1 = len(xs)
all_patches = [] #for items in a single legend
# Create figure and `ax` for map plotting
# This form can create a single axes or an array of axes
fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(8,6), subplot_kw={'projection': ccrs.PlateCarree()})
# All steps of plots will be done on `ax`
# [1] Add an invisible object as a spacer in the legend box
#rect = mpatches.Rectangle([0, 0], 0.01, 0.01, ec="none", color="lightgray")
all_patches.append(mlines.Line2D([0, 0], [1, 0], color="none"))
# Explicitly defining the elements in the legend
# [2] Add proxied text: 'Categories' to the legend
line = mlines.Line2D([0, 0], [1, 0], lw=.5, alpha=0.9, color="none")
line.set_label('Categories') # Title for 1st group of symbols in the legend
all_patches.append(line)
# [3] Plot (on the axes) `none` data point and
# save the output patches for `Categories` group
patches_V = [ ax.plot([],[], marker=marker_V[i], ms=8, ls="", color=color_V[i], \
label="{:s}".format(text_V[i]) )[0] \
for i in range(len_V) ]
all_patches += patches_V
# [4] Add an invisible object as a spacer in the legend box
all_patches.append(mlines.Line2D([0, 0], [1, 0], color="none"))
# [5] Add proxied text: 'Sizes' to the legend
x, y = ([0, 1], [0, 0])
line = mlines.Line2D([0, 0], [1, 0], lw=.5, alpha=0.9, color="none")
line.set_label('Sizes') # Title for 2nd group of symbols in the legend
all_patches.append(line)
# [6] Create patches for `Sizes` group
patches_S = [ ax.plot([],[], marker=marker_S[i], ms=sizes_S[i], ls="", \
color=color_S[i], \
label="{:s}".format(text_S[i]) )[0] for i in range(len_S) ]
all_patches += patches_S
# Plot point data using the demo data
for i in range(len1):
ax.plot(xs[i], ys[i], marker=markers1[i], ms=sizes1[i], color=colors1[i])
ax.set_extent([0, 80, 0, 60])
# Plot the legend in the upper-right corner
combined_legend = ax.legend(handles=all_patches,
bbox_to_anchor=(1, 1),
title="The Legend",
loc='upper right',
ncol=1,
numpoints=1,
facecolor="lightgray",
fontsize = 10,
title_fontsize= 12,
labelspacing = 0.55,
shadow=True)
# Draw some basemap features
ax.coastlines(lw=0.3, color="k")
ax.add_feature(cfeature.LAND)
ax.add_feature(cfeature.OCEAN)
plt.title("Legend for Categories and Sizes")
plt.show()
The output map: