Note
This page was generated from gallery/plotting_with_geoplot.ipynb.
Interactive online version: 
Plotting with Geoplot and GeoPandas#
Geoplot is a Python library providing a selection of easy-to-use geospatial visualizations. It is built on top of the lower-level CartoPy, covered in a separate section of this tutorial, and is designed to work with GeoPandas input.
This example is a brief tour of the geoplot API. For more details on the library refer to its documentation.
First we’ll load in the data using GeoPandas.
[1]:
import geopandas
import geodatasets
import geoplot
world = geopandas.read_file("https://naciscdn.org/naturalearth/110m/cultural/ne_110m_admin_0_countries.zip")
boroughs = geopandas.read_file(geoplot.datasets.get_path("nyc_boroughs"))
collisions = geopandas.read_file(geoplot.datasets.get_path("nyc_injurious_collisions"))
ERROR 1: PROJ: proj_create_from_database: Open of /home/docs/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/share/proj failed
Plotting with Geoplot#
We start out by replicating the basic GeoPandas world plot using Geoplot.
[2]:
geoplot.polyplot(world, figsize=(8, 4))
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/geoplot/geoplot.py:885, in polyplot.<locals>.PolyPlot.draw(self)
884 try: # Duck test for MultiPolygon.
--> 885 for subgeom in geom:
886 feature = GeopandasPolygonPatch(
887 subgeom, facecolor=facecolor, edgecolor=edgecolor, zorder=zorder,
888 **kwargs
889 )
TypeError: 'MultiPolygon' object is not iterable
During handling of the above exception, another exception occurred:
AttributeError Traceback (most recent call last)
Cell In[2], line 1
----> 1 geoplot.polyplot(world, figsize=(8, 4))
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/geoplot/geoplot.py:901, in polyplot(df, projection, extent, figsize, ax, **kwargs)
898 return ax
900 plot = PolyPlot(df, figsize=figsize, ax=ax, extent=extent, projection=projection, **kwargs)
--> 901 return plot.draw()
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/geoplot/geoplot.py:892, in polyplot.<locals>.PolyPlot.draw(self)
890 ax.add_patch(feature)
891 except (TypeError, AssertionError): # Shapely Polygon.
--> 892 feature = GeopandasPolygonPatch(
893 geom, facecolor=facecolor, edgecolor=edgecolor, zorder=zorder,
894 **kwargs
895 )
896 ax.add_patch(feature)
898 return ax
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/geopandas/plotting.py:130, in _PolygonPatch(polygon, **kwargs)
126 from matplotlib.patches import PathPatch
127 from matplotlib.path import Path
129 path = Path.make_compound_path(
--> 130 Path(np.asarray(polygon.exterior.coords)[:, :2]),
131 *[Path(np.asarray(ring.coords)[:, :2]) for ring in polygon.interiors],
132 )
133 return PathPatch(path, **kwargs)
AttributeError: 'MultiPolygon' object has no attribute 'exterior'
Geoplot can re-project data into any of the map projections provided by CartoPy (see the list here).
[3]:
# use the Orthographic map projection (e.g. a world globe)
ax = geoplot.polyplot(world, projection=geoplot.crs.Orthographic(), figsize=(8, 4))
ax.outline_patch.set_visible(True)
/home/docs/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/geoplot/geoplot.py:703: UserWarning: Plot extent lies outside of the Orthographic projection's viewport. Defaulting to global extent.
warnings.warn(
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[3], line 3
1 # use the Orthographic map projection (e.g. a world globe)
2 ax = geoplot.polyplot(world, projection=geoplot.crs.Orthographic(), figsize=(8, 4))
----> 3 ax.outline_patch.set_visible(True)
AttributeError: 'GeoAxes' object has no attribute 'outline_patch'
polyplot is trivial and can only plot the geometries you pass to it. If you want to use color as a visual variable, specify a choropleth. Here we sort GDP per person by country into five buckets by color, using “quantiles” binning from the Mapclassify library.
[4]:
import mapclassify
gpd_per_person = world["gdp_md_est"] / world["pop_est"]
scheme = mapclassify.Quantiles(gpd_per_person, k=5)
# Note: this code sample requires geoplot>=0.4.0.
geoplot.choropleth(
world, hue=gpd_per_person, scheme=scheme, cmap="Greens", figsize=(8, 4)
)
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/indexes/base.py:3802, in Index.get_loc(self, key)
3801 try:
-> 3802 return self._engine.get_loc(casted_key)
3803 except KeyError as err:
File index.pyx:153, in pandas._libs.index.IndexEngine.get_loc()
File index.pyx:182, in pandas._libs.index.IndexEngine.get_loc()
File pandas/_libs/hashtable_class_helper.pxi:7081, in pandas._libs.hashtable.PyObjectHashTable.get_item()
File pandas/_libs/hashtable_class_helper.pxi:7089, in pandas._libs.hashtable.PyObjectHashTable.get_item()
KeyError: 'gdp_md_est'
The above exception was the direct cause of the following exception:
KeyError Traceback (most recent call last)
Cell In[4], line 3
1 import mapclassify
----> 3 gpd_per_person = world["gdp_md_est"] / world["pop_est"]
4 scheme = mapclassify.Quantiles(gpd_per_person, k=5)
6 # Note: this code sample requires geoplot>=0.4.0.
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/geopandas/geodataframe.py:1456, in GeoDataFrame.__getitem__(self, key)
1450 def __getitem__(self, key):
1451 """
1452 If the result is a column containing only 'geometry', return a
1453 GeoSeries. If it's a DataFrame with any columns of GeometryDtype,
1454 return a GeoDataFrame.
1455 """
-> 1456 result = super().__getitem__(key)
1457 # Custom logic to avoid waiting for pandas GH51895
1458 # result is not geometry dtype for multi-indexes
1459 if (
1460 pd.api.types.is_scalar(key)
1461 and key == ""
(...)
1464 and not is_geometry_type(result)
1465 ):
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/frame.py:4090, in DataFrame.__getitem__(self, key)
4088 if self.columns.nlevels > 1:
4089 return self._getitem_multilevel(key)
-> 4090 indexer = self.columns.get_loc(key)
4091 if is_integer(indexer):
4092 indexer = [indexer]
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/indexes/base.py:3809, in Index.get_loc(self, key)
3804 if isinstance(casted_key, slice) or (
3805 isinstance(casted_key, abc.Iterable)
3806 and any(isinstance(x, slice) for x in casted_key)
3807 ):
3808 raise InvalidIndexError(key)
-> 3809 raise KeyError(key) from err
3810 except TypeError:
3811 # If we have a listlike key, _check_indexing_error will raise
3812 # InvalidIndexError. Otherwise we fall through and re-raise
3813 # the TypeError.
3814 self._check_indexing_error(key)
KeyError: 'gdp_md_est'
If you want to use size as a visual variable, use a cartogram. Here are population estimates for countries in Africa.
[5]:
africa = world.query('continent == "Africa"')
ax = geoplot.cartogram(
africa, scale="pop_est", limits=(0.2, 1), edgecolor="None", figsize=(7, 8)
)
geoplot.polyplot(africa, edgecolor="gray", ax=ax)
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/scope.py:231, in Scope.resolve(self, key, is_local)
230 if self.has_resolvers:
--> 231 return self.resolvers[key]
233 # if we're here that means that we have no locals and we also have
234 # no resolvers
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/collections/__init__.py:1006, in ChainMap.__getitem__(self, key)
1005 pass
-> 1006 return self.__missing__(key)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/collections/__init__.py:998, in ChainMap.__missing__(self, key)
997 def __missing__(self, key):
--> 998 raise KeyError(key)
KeyError: 'continent'
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/scope.py:242, in Scope.resolve(self, key, is_local)
238 try:
239 # last ditch effort we look in temporaries
240 # these are created when parsing indexing expressions
241 # e.g., df[df > 0]
--> 242 return self.temps[key]
243 except KeyError as err:
KeyError: 'continent'
The above exception was the direct cause of the following exception:
UndefinedVariableError Traceback (most recent call last)
Cell In[5], line 1
----> 1 africa = world.query('continent == "Africa"')
2 ax = geoplot.cartogram(
3 africa, scale="pop_est", limits=(0.2, 1), edgecolor="None", figsize=(7, 8)
4 )
5 geoplot.polyplot(africa, edgecolor="gray", ax=ax)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/frame.py:4811, in DataFrame.query(self, expr, inplace, **kwargs)
4809 kwargs["level"] = kwargs.pop("level", 0) + 1
4810 kwargs["target"] = None
-> 4811 res = self.eval(expr, **kwargs)
4813 try:
4814 result = self.loc[res]
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/frame.py:4937, in DataFrame.eval(self, expr, inplace, **kwargs)
4934 kwargs["target"] = self
4935 kwargs["resolvers"] = tuple(kwargs.get("resolvers", ())) + resolvers
-> 4937 return _eval(expr, inplace=inplace, **kwargs)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/eval.py:336, in eval(expr, parser, engine, local_dict, global_dict, resolvers, level, target, inplace)
327 # get our (possibly passed-in) scope
328 env = ensure_scope(
329 level + 1,
330 global_dict=global_dict,
(...)
333 target=target,
334 )
--> 336 parsed_expr = Expr(expr, engine=engine, parser=parser, env=env)
338 if engine == "numexpr" and (
339 is_extension_array_dtype(parsed_expr.terms.return_type)
340 or getattr(parsed_expr.terms, "operand_types", None) is not None
(...)
344 )
345 ):
346 warnings.warn(
347 "Engine has switched to 'python' because numexpr does not support "
348 "extension array dtypes. Please set your engine to python manually.",
349 RuntimeWarning,
350 stacklevel=find_stack_level(),
351 )
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/expr.py:809, in Expr.__init__(self, expr, engine, parser, env, level)
807 self.parser = parser
808 self._visitor = PARSERS[parser](self.env, self.engine, self.parser)
--> 809 self.terms = self.parse()
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/expr.py:828, in Expr.parse(self)
824 def parse(self):
825 """
826 Parse an expression.
827 """
--> 828 return self._visitor.visit(self.expr)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/expr.py:412, in BaseExprVisitor.visit(self, node, **kwargs)
410 method = f"visit_{type(node).__name__}"
411 visitor = getattr(self, method)
--> 412 return visitor(node, **kwargs)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/expr.py:418, in BaseExprVisitor.visit_Module(self, node, **kwargs)
416 raise SyntaxError("only a single expression is allowed")
417 expr = node.body[0]
--> 418 return self.visit(expr, **kwargs)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/expr.py:412, in BaseExprVisitor.visit(self, node, **kwargs)
410 method = f"visit_{type(node).__name__}"
411 visitor = getattr(self, method)
--> 412 return visitor(node, **kwargs)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/expr.py:421, in BaseExprVisitor.visit_Expr(self, node, **kwargs)
420 def visit_Expr(self, node, **kwargs):
--> 421 return self.visit(node.value, **kwargs)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/expr.py:412, in BaseExprVisitor.visit(self, node, **kwargs)
410 method = f"visit_{type(node).__name__}"
411 visitor = getattr(self, method)
--> 412 return visitor(node, **kwargs)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/expr.py:719, in BaseExprVisitor.visit_Compare(self, node, **kwargs)
717 op = self.translate_In(ops[0])
718 binop = ast.BinOp(op=op, left=node.left, right=comps[0])
--> 719 return self.visit(binop)
721 # recursive case: we have a chained comparison, a CMP b CMP c, etc.
722 left = node.left
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/expr.py:412, in BaseExprVisitor.visit(self, node, **kwargs)
410 method = f"visit_{type(node).__name__}"
411 visitor = getattr(self, method)
--> 412 return visitor(node, **kwargs)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/expr.py:532, in BaseExprVisitor.visit_BinOp(self, node, **kwargs)
531 def visit_BinOp(self, node, **kwargs):
--> 532 op, op_class, left, right = self._maybe_transform_eq_ne(node)
533 left, right = self._maybe_downcast_constants(left, right)
534 return self._maybe_evaluate_binop(op, op_class, left, right)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/expr.py:452, in BaseExprVisitor._maybe_transform_eq_ne(self, node, left, right)
450 def _maybe_transform_eq_ne(self, node, left=None, right=None):
451 if left is None:
--> 452 left = self.visit(node.left, side="left")
453 if right is None:
454 right = self.visit(node.right, side="right")
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/expr.py:412, in BaseExprVisitor.visit(self, node, **kwargs)
410 method = f"visit_{type(node).__name__}"
411 visitor = getattr(self, method)
--> 412 return visitor(node, **kwargs)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/expr.py:545, in BaseExprVisitor.visit_Name(self, node, **kwargs)
544 def visit_Name(self, node, **kwargs) -> Term:
--> 545 return self.term_type(node.id, self.env, **kwargs)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/ops.py:91, in Term.__init__(self, name, env, side, encoding)
89 tname = str(name)
90 self.is_local = tname.startswith(LOCAL_TAG) or tname in DEFAULT_GLOBALS
---> 91 self._value = self._resolve_name()
92 self.encoding = encoding
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/ops.py:115, in Term._resolve_name(self)
110 if local_name in self.env.scope and isinstance(
111 self.env.scope[local_name], type
112 ):
113 is_local = False
--> 115 res = self.env.resolve(local_name, is_local=is_local)
116 self.update(res)
118 if hasattr(res, "ndim") and res.ndim > 2:
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/pandas/core/computation/scope.py:244, in Scope.resolve(self, key, is_local)
242 return self.temps[key]
243 except KeyError as err:
--> 244 raise UndefinedVariableError(key, is_local) from err
UndefinedVariableError: name 'continent' is not defined
If we have data in the shape of points in space, we may generate a three-dimensional heatmap on it using kdeplot.
[6]:
ax = geoplot.kdeplot(
collisions.head(1000),
clip=boroughs.geometry,
shade=True,
cmap="Reds",
projection=geoplot.crs.AlbersEqualArea(),
)
geoplot.polyplot(boroughs, ax=ax, zorder=1)
/home/docs/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/geoplot/geoplot.py:1304: FutureWarning:
`shade` is now deprecated in favor of `fill`; setting `fill=True`.
This will become an error in seaborn v0.14.0; please update your code.
sns.kdeplot(
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[6], line 1
----> 1 ax = geoplot.kdeplot(
2 collisions.head(1000),
3 clip=boroughs.geometry,
4 shade=True,
5 cmap="Reds",
6 projection=geoplot.crs.AlbersEqualArea(),
7 )
8 geoplot.polyplot(boroughs, ax=ax, zorder=1)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/geoplot/geoplot.py:1320, in kdeplot(df, projection, extent, figsize, ax, clip, **kwargs)
1315 return ax
1317 plot = KDEPlot(
1318 df, projection=projection, extent=extent, figsize=figsize, ax=ax, clip=clip, **kwargs
1319 )
-> 1320 return plot.draw()
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/geoplot/geoplot.py:1304, in kdeplot.<locals>.KDEPlot.draw(self)
1301 return ax
1303 if self.projection:
-> 1304 sns.kdeplot(
1305 x=pd.Series([p.x for p in self.df.geometry]),
1306 y=pd.Series([p.y for p in self.df.geometry]),
1307 transform=ccrs.PlateCarree(), ax=ax, **self.kwargs
1308 )
1309 else:
1310 sns.kdeplot(
1311 x=pd.Series([p.x for p in self.df.geometry]),
1312 y=pd.Series([p.y for p in self.df.geometry]),
1313 ax=ax, **self.kwargs
1314 )
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/seaborn/distributions.py:1682, in kdeplot(data, x, y, hue, weights, palette, hue_order, hue_norm, color, fill, multiple, common_norm, common_grid, cumulative, bw_method, bw_adjust, warn_singular, log_scale, levels, thresh, gridsize, cut, clip, legend, cbar, cbar_ax, cbar_kws, ax, **kwargs)
1679 p._attach(ax, allowed_types=["numeric", "datetime"], log_scale=log_scale)
1681 method = ax.fill_between if fill else ax.plot
-> 1682 color = _default_color(method, hue, color, kwargs)
1684 if not p.has_xy_data:
1685 return ax
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/seaborn/utils.py:136, in _default_color(method, hue, color, kws, saturation)
133 elif method.__name__ == "fill_between":
135 kws = normalize_kwargs(kws, mpl.collections.PolyCollection)
--> 136 scout = method([], [], **kws)
137 facecolor = scout.get_facecolor()
138 color = to_rgb(facecolor[0])
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/matplotlib/__init__.py:1465, in _preprocess_data.<locals>.inner(ax, data, *args, **kwargs)
1462 @functools.wraps(func)
1463 def inner(ax, *args, data=None, **kwargs):
1464 if data is None:
-> 1465 return func(ax, *map(sanitize_sequence, args), **kwargs)
1467 bound = new_sig.bind(ax, *args, **kwargs)
1468 auto_label = (bound.arguments.get(label_namer)
1469 or bound.kwargs.get(label_namer))
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/matplotlib/axes/_axes.py:5509, in Axes.fill_between(self, x, y1, y2, where, interpolate, step, **kwargs)
5507 def fill_between(self, x, y1, y2=0, where=None, interpolate=False,
5508 step=None, **kwargs):
-> 5509 return self._fill_between_x_or_y(
5510 "x", x, y1, y2,
5511 where=where, interpolate=interpolate, step=step, **kwargs)
File ~/checkouts/readthedocs.org/user_builds/geopandas/conda/stable/lib/python3.11/site-packages/matplotlib/axes/_axes.py:5500, in Axes._fill_between_x_or_y(self, ind_dir, ind, dep1, dep2, where, interpolate, step, **kwargs)
5498 up_x = up_y = True
5499 if "transform" in kwargs:
-> 5500 up_x, up_y = kwargs["transform"].contains_branch_seperately(self.transData)
5501 self.update_datalim(pts, updatex=up_x, updatey=up_y)
5503 self.add_collection(collection, autolim=False)
AttributeError: 'PlateCarree' object has no attribute 'contains_branch_seperately'
These are just some of the plots you can make with Geoplot. There are many other possibilities not covered in this brief introduction. For more examples, refer to the Gallery in the Geoplot documentation.