GeoArrow Pandas

Common errors

• TypeError: cannot convert '...' to GeoArrowExtensionDtype

  cause The data being passed to `pd.Series` (or similar constructor) is not in a format that `geoarrow-pandas` can directly convert into a GeoArrow extension type.
  fix Ensure your input data is a list of `shapely` geometries, WKB/WKT strings, or a compatible PyArrow array. Explicitly specify the GeoArrow dtype, e.g., `pd.Series([...], dtype=ga.wkb_type())` or `pd.Series([...], dtype=ga.point_type(pyarrow.float64()))`.

• AttributeError: 'GeoArrowExtensionArray' object has no attribute 'area'

  cause You are attempting to call a geometry-specific method (like `.area`, `.centroid`, etc.) directly on the `GeoArrowExtensionArray` or its accessor, expecting GeoPandas-like behavior.
  fix GeoArrow Pandas provides a memory-efficient backbone, but does not replicate all GeoPandas geometry methods directly. Convert your data to a `geopandas.GeoDataFrame` or `GeoSeries` first using `ga.to_geopandas()` if you need these methods, or use lower-level functions from the `geoarrow` library itself for spatial operations.

• ModuleNotFoundError: No module named 'geoarrow.pandas'

  cause The `geoarrow-pandas` library has not been installed in your current Python environment.
  fix Install the library using pip: `pip install geoarrow-pandas`.

Warnings

• breaking As a '0.x' experimental library, the API of geoarrow-pandas is subject to change without strict backward compatibility guarantees. Expect potential modifications to class names, function signatures, and overall structure in future releases.
  Fix: Always review release notes for new versions. Pin specific minor versions in your dependencies to mitigate unexpected changes for a period.
• gotcha Direct conversion of large GeoArrow-backed DataFrames or Series to GeoPandas (e.g., via `ga.to_geopandas`) can be computationally intensive and memory-hungry, as it often involves copying data and converting it to shapely objects.
  Fix: For operations primarily within the GeoArrow ecosystem, try to avoid frequent conversions to GeoPandas. Convert only when specific GeoPandas functionality is required. Consider processing data in chunks or streaming if memory becomes an issue.
• gotcha GeoArrow-backed Series (GeoArrowExtensionDtype) do not expose the same comprehensive set of geometry-specific methods (e.g., `.area`, `.centroid`, `.crs`) directly on the Series accessor as a `geopandas.GeoSeries` does.
  Fix: To access these methods, you may need to explicitly convert the GeoArrow Series to a `geopandas.GeoSeries` using `ga.to_geopandas()` (if the input is a DataFrame/Series) or access the underlying GeoArrowArray for lower-level operations. Many spatial operations can also be performed via the `geoarrow` library itself.
• gotcha Attempting to create a GeoArrowExtensionDtype Series with incompatible Python objects or incorrect `pyarrow` types can lead to `TypeError` or `ValueError`.
  Fix: Ensure that the input data (e.g., list of shapely objects) is compatible with the chosen GeoArrow type (e.g., `ga.wkb_type()`). If working with PyArrow arrays directly, ensure they conform to the GeoArrow specifications.

Install

• pip install geoarrow-pandas Install stable version

Imports

• geoarrow.pandas

  import geoarrow.pandas as ga

• GeoArrowExtensionDtype
  wrong:

  from geoarrow.pandas.types import GeoArrowExtensionDtype

  correct:

  from geoarrow.pandas import GeoArrowExtensionDtype

  The primary types are exposed directly under `geoarrow.pandas` for convenience.

Quickstart

This quickstart demonstrates how to create a pandas Series using GeoArrow extension types, specifically the Well-Known Binary (WKB) format. It uses `shapely` to construct geometries and `ga.wkb_type()` to specify the GeoArrow dtype. The series will behave like a regular pandas Series but with GeoArrow's efficient backing.

import pandas as pd
import geoarrow.pandas as ga
import shapely

# Create a pandas Series with GeoArrow-backed WKB geometries
s = pd.Series([shapely.Point(1, 2), shapely.Point(3, 4)], dtype=ga.wkb_type())

print("GeoArrow-backed Series:")
print(s)
print(f"Series dtype: {s.dtype}")

# Example conversion to GeoPandas
# geopandas dependency would be needed for actual usage:
# try:
#     import geopandas
#     gdf = ga.to_geopandas(s.to_frame(name='geometry'))
#     print('\nConverted to GeoPandas GeoDataFrame:')
#     print(gdf)
# except ImportError:
#     print('\nSkipping GeoPandas conversion (geopandas not installed).')