How to Save and Export Cartogram Results¶

Once you have a cartogram you're happy with, you'll want to either save it for later or export it to a GIS format. This guide shows both options:

1. Save and reload — preserves the full Cartogram object (errors, history, options)
2. Export to GeoDataFrame — converts morphed geometries to a table you can plot or save to file

In [1]:

import carto_flow.data as examples
import carto_flow.flow_cartogram as flow

import carto_flow.data as examples import carto_flow.flow_cartogram as flow

In [2]:

gdf = examples.load_us_census(population=True)
cartogram = flow.morph_gdf(gdf, "Population")

gdf = examples.load_us_census(population=True) cartogram = flow.morph_gdf(gdf, "Population")

Morph geometries:  22%|████▍               | 112/500 [00:03<00:13, 29.58it/s, max=1.2%, mean=0.2% - converged]

Option 1: Save and reload the Cartogram object¶

cartogram.save() writes the result to a JSON file that can be reloaded with Cartogram.load(). This preserves everything: morphed geometries, error history, convergence data, and the options used.

In [3]:

cartogram.save("my_cartogram.json")

# Later, in another session:
loaded = flow.Cartogram.load("my_cartogram.json")
print("Status after reload:", loaded.status)
print("Mean error:", loaded.get_errors().mean_error_pct, "%")

cartogram.save("my_cartogram.json") # Later, in another session: loaded = flow.Cartogram.load("my_cartogram.json") print("Status after reload:", loaded.status) print("Mean error:", loaded.get_errors().mean_error_pct, "%")

Status after reload: converged
Mean error: 0.2327604968295871 %

Option 2: Export to GeoDataFrame¶

to_geodataframe() returns the morphed geometries as a GeoDataFrame with the original columns plus error and density columns. From there, you can write to any format GeoPandas supports.

In [4]:

result_gdf = cartogram.to_geodataframe()
print(result_gdf.columns.tolist())
result_gdf.head(3)

result_gdf = cartogram.to_geodataframe() print(result_gdf.columns.tolist()) result_gdf.head(3)

['STATE', 'State Name', 'Population', 'geometry', 'State Abbreviation', 'Population (Millions)', 'Population Density', '_morph_error_pct', '_morph_density']

Out[4]:

	STATE	State Name	Population	geometry	State Abbreviation	Population (Millions)	Population Density	_morph_error_pct	_morph_density
0	42	Pennsylvania	12794885	POLYGON ((888717.564 266417.625, 888385.153 26...	PA	12.794885	109.040911	-0.133324	0.000042
1	06	California	39346023	MULTIPOLYGON (((-1880692.408 -525043.318, -188...	CA	39.346023	96.008122	-0.026952	0.000042
2	54	West Virginia	1807426	POLYGON ((784468.649 -222213.647, 784493.514 -...	WV	1.807426	28.801063	-0.062484	0.000042

In [5]:

# Write to GeoPackage for use in QGIS, ArcGIS, etc.
result_gdf.to_file("cartogram.gpkg", driver="GPKG")

# Or to GeoJSON for web maps
result_gdf.to_file("cartogram.geojson", driver="GeoJSON")

# Write to GeoPackage for use in QGIS, ArcGIS, etc. result_gdf.to_file("cartogram.gpkg", driver="GPKG") # Or to GeoJSON for web maps result_gdf.to_file("cartogram.geojson", driver="GeoJSON")

Quick check: plot the reloaded result¶

Verify the save/load round-trip by plotting the reloaded cartogram.

In [10]:

import matplotlib.pyplot as plt

fig, axes = plt.subplots(1, 2, figsize=(14, 5))

cartogram.plot("Population (Millions)", ax=axes[0], cmap="RdYlGn_r", legend=True, vmin=0, vmax=40)
axes[0].set(title="Original")
axes[0].axis("off")

loaded.to_geodataframe().plot("Population (Millions)", ax=axes[1], cmap="RdYlGn_r", legend=True, vmin=0, vmax=40)
axes[1].set(title="Cartogram (reloaded)")
axes[1].axis("off")

plt.tight_layout();

import matplotlib.pyplot as plt fig, axes = plt.subplots(1, 2, figsize=(14, 5)) cartogram.plot("Population (Millions)", ax=axes[0], cmap="RdYlGn_r", legend=True, vmin=0, vmax=40) axes[0].set(title="Original") axes[0].axis("off") loaded.to_geodataframe().plot("Population (Millions)", ax=axes[1], cmap="RdYlGn_r", legend=True, vmin=0, vmax=40) axes[1].set(title="Cartogram (reloaded)") axes[1].axis("off") plt.tight_layout();

In [ ]: