How to create a single figure legend for GeoAxes subplots

Question

I have looked at the many other questions on here to try and solve this but for whatever reason I cannot. Each solution seems to give me the same error, or returns nothing at all.

I have a list of six dataframes I am looping through to create a figure of 6 maps. Each dataframe is formatted similar with the only differenc being their temporal column. Each map has the same classification scheme created through cartopy. The colors are determined with a colormap, the dataframe itself has no colors related to the values. I want a singular legend for all the maps, so that it is more visible to readers, and less redundant. Here is my code:

import cartopy.crs as ccrs
import cartopy.feature as cfeature
import mapclassify
from matplotlib.colors import rgb2hex
from matplotlib.colors import ListedColormap
plt.style.use('seaborn-v0_8-dark')

# Define the Robinson projection
robinson = ccrs.Robinson()

# Create a 3x2 grid of subplots
fig, axs = plt.subplots(3, 2, figsize=(12, 12), subplot_kw={'projection': robinson})

# Flatten the subplot array for easy iteration
axs = axs.flatten()


# Define color map and how many bins needed
cmap = plt.cm.get_cmap('YlOrRd', 5) #Blues #Greens #PuRd #YlOrRd
# Any countries with NaN values will be colored grey
missing_kwds = dict(color='grey', label='No Data')


# Loop through the dataframes and create submaps
for i, df in enumerate(dataframes):
    
    # Create figure and axis with Robinson projection
    mentionsgdf_robinson = df.to_crs(robinson.proj4_init)
    
   
    # Plot the submap
    ax = axs[i]
    
    # Add land mask and gridlines
    ax.add_feature(cfeature.LAND.with_scale('50m'), facecolor='lightgrey')
    gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=True,
                  linewidth=1, color='gray', alpha=0.3, linestyle='--')
    
    gl.xlabel_style = {'fontsize': 7}
    gl.ylabel_style = {'fontsize': 7}
    
    # Classification scheme options: EqualInterval, Quantiles, NaturalBreaks, UserDefined etc.
    mentionsgdf_robinson.plot(column='mentions', 
                              ax=ax, 
                              legend=True, #True
                              cmap=cmap, 
                              legend_kwds=({"loc":'center left', 'title': 'Number of Mentions', 'prop': {'size': 7, 'family': 'serif'}}),
                              missing_kwds=missing_kwds,
                              scheme="UserDefined", 
                              classification_kwds = {'bins':[20, 50, 150, 300, 510]})
    
    # Set the titles of each submap
    ax.set_title(f'20{i+15}', size = 15, family = 'Serif')
    
    # Define the bounds of the classification scheme
    upper_bounds = mapclassify.UserDefined(mentionsgdf_robinson.mentions, bins=[20, 50, 150, 300, 510]).bins
    
    
    bounds = []
    for index, upper_bound in enumerate(upper_bounds):
        if index == 0:
            lower_bound = mentionsgdf_robinson.mentions.min()
        else:
            lower_bound = upper_bounds[index-1]

        bound = f'{lower_bound:.0f} - {upper_bound:.0f}'
        bounds.append(bound)
    
    # replace the legend title and increase font size
    legend_title = ax.get_legend().get_title()
    legend_title.set_fontsize(8)
    legend_title.set_family('serif')
    
    
    # get all the legend labels and increase font size
    legend_labels = ax.get_legend().get_texts()
    # replace the legend labels
    for bound, legend_label in zip(bounds, legend_labels):
        legend_label.set_text(bound)
    


fig.suptitle(' Yearly Country Mentions in Online News about Species Threatened by Trade ', fontsize=15, family = 'Serif')
    
# Adjust spacing between subplots
plt.tight_layout(pad=4.0)

# Save the figure
#plt.savefig('figures/submaps_5years.png', dpi=300)

# Show the submap
plt.show()

And here is my result as of right now. I would like to have just one legend somewhere to the side of center of the maps.

I have tried this code as suggested here but only received a UserWarning: Legend does not support handles for PatchCollection instances. Also I didn't know how to possibly incorporate all the other modifications I need for the legend outside of the loop (bounds, font, bins, etc.)

handles, labels = ax.get_legend_handles_labels()
fig.legend(handles, labels, loc='upper center')

Here's data for three years 2015-2017: https://jmp.sh/s/ohkSJpaMZ4c1GifIX0nu

Here's all the files for the global shapefile that I've used: https://jmp.sh/uTP9DZsC

Using this data and the following code should allow you to run the full visualization code shared above. Thank you.

import geopandas as gpd
import pandas as pd

# Read in globe shapefile dataframe 
world = gpd.read_file("TM_WORLD_BORDERS-0.3.shp")
# Read in sample dataframe
df = pd.read_csv("fifsixseventeen.csv", sep = ";")

# Separate according to date column 
fifteen = df[(df['date'] == 2015)].reset_index(drop=True)
sixteen = df[(df['date'] == 2016)].reset_index(drop=True)
seventeen = df[(df['date'] == 2017)].reset_index(drop=True)

# Function to merge isocodes of the countries with world shapefile 
def merge_isocodes(df):
    
    # Groupby iso3 column in order to merge with shapefile
    allmentions = df.groupby("iso3")['mentions'].sum().sort_values(ascending = False).reset_index()

    # Merge on iso3 code 
    mentionsgdf = pd.merge(allmentions, world, left_on=allmentions["iso3"], right_on=world["ISO3"], how="right").drop(columns = "key_0")

    # Redefine as a geodataframe
    mentionsgdf = gpd.GeoDataFrame(mentionsgdf, geometry='geometry')
    
    return mentionsgdf

onefive = merge_isocodes(fifteen)
onesix = merge_isocodes(sixteen)
oneseven = merge_isocodes(seventeen)

# Create a list to store each years' dataframes
dataframes = [onefive, onesix, oneseven]

Answer 1

• These Axes are cartopy.mpl.geoaxes.GeoAxes
  • axs[0].get_legend_handles_labels() results in UserWarning: Legend does not support handles for PatchCollection instances., and returns ([], []).
• Use Axes.get_legend() to get the Legend instance.
  • .legend_handles is new in matplotlib 3.7.2 and returns the list of Artist objects. Alternatively, use .legendHandles, but it is deprecated.
• See How to put the legend outside the plot for details about positioning the legend.
  • Also relevant, Moving matplotlib legend outside of the axis makes it cutoff by the figure box: fig.savefig('fig.png', bbox_inches='tight')
• Caveat: assumes all legends are the same.
• Tested in python 3.9.18, geopandas 0.12.2, matplotlib 3.7.2, cartopy 0.22.0.

... 

for i, df in enumerate(dataframes):
    ...

# after the for loop, use the following code

# extract the legend from an axes - used the last axes for the smaller sample data
l = axs[2].get_legend()
# extract the handles
handles = l.legend_handles
# get the label text
labels = [v.get_text() for v in l.texts]
# get the title text
title = l.get_title().get_text()
# create the figure legend
fig.legend(title=title, handles=handles, labels=labels, bbox_to_anchor=(1, 0.5), loc='center left', frameon=False)

# iterate through each Axes
for ax in axs:
    # if the legend isn't None (if this condition isn't required, remove it and use only ax.get_legend().remove()) 
    if gt := ax.get_legend():
        # remove the legend
        gt.remove()

Answer 2

This might not be the workaround you are looking for, but one I have implemented successfully in the past. Essentially, you place only one subplot's legend, and manually manipulate its position and size to fall outside of the single subplot in an appropriate place for the whole figure.

Use the bounding box function: bbox_to_anchor() to place the legend outside of the subplot you chose.

Then, switch from data to axis coordinates using transform argument. Specifically, if placed with respect to the coordinates of axs[k], then the code could look like:

axs[k].legend(bbox_to_anchor = (m,n), transform=axs[k].transAxes, borderaxespad=0)

where m and n are floats that control the legend position. These (in my experience) are often determined through trial and error.

Further reading & implementation from mpl documentation can be found here.