esda

library2.9.0pypypi✓ verified 86d ago

esda is a Python library implementing methods for exploratory spatial data analysis, part of the PySAL family. It provides global and local spatial autocorrelation statistics (Moran's I, Geary's C, Getis-Ord G, etc.), spatial correlograms, and shape-based measures. Current version is 2.9.0, requires Python >=3.11. Releases follow a monthly-to-quarterly cadence, with active maintenance.

data

pip install esda

github ↗package ↗homepage ↗

INSTALL

IMPORT

SIG · ESDA

esda

datapythonv2.9.0

Install

16.9s avg

Import

5569ms

Disk

515MB

Pass rate

5/ 10

Env Coverage5 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v2.7.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.910 runs

build_error

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 16.9s · import 5.569s · 504MB

515MB installed

● package 515MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Moran

✓ from esda import Moran

Moran_Local

✓ from esda import Moran_Local

✗ from esda.moran import Moran_Local

Moran_Local is directly importable from esda since v2.0.

Geary

✓ from esda import Geary

Getis_Ord_G

✓ from esda import Getis_Ord_G

Compute Global Moran's I with a K-nearest neighbors weight matrix.

import libpysal from esda import Moran import numpy as np # Generate random data and a spatial weights matrix np.random.seed(123) y = np.random.random(100) w = libpysal.weights.KNN(k=5, ids=np.arange(100)) # Compute Global Moran's I mi = Moran(y, w) print(f"Moran's I: {mi.I:.3f}, p-value: {mi.p_sim:.3f}") # Output: Moran's I: -0.022, p-value: 0.632

Debug

Known issues

breakingIn esda>=2.5, shapely>=2 is required and pygeos is no longer supported. Upgrade shapely or pin shapely<2.

fix

pip install shapely>=2 or ensure you have a compatible version.

affects: >=2.5.0

gotchaMoran_Local (Local Moran's I) uses a randomization-based p-value by default. For analytical p-values, set `permutations=0` when constructing the object.

fix

moran_local = Moran_Local(y, w, permutations=0)

affects: all

gotchaThe `spatial_lag` function is not a separate function; use `libpysal.weights.lag_spatial(w, y)` instead.

fix

import libpysal; lag = libpysal.weights.lag_spatial(w, y)

affects: all

deprecatedThe `assuncao_rate` function is deprecated since version 2.5. Please use `esda.rate_smoothing.assuncao_rate` instead.

fix

from esda.rate_smoothing import assuncao_rate

affects: >=2.5.0

gotchaWhen using `Moran_Local.plot()` or `Moran_Local.scatterplot()`, ensure matplotlib is installed. These are available since v2.7.

fix

pip install matplotlib

affects: >=2.7.0

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'esda.moran'

Trying to import Moran_Local from the wrong submodule.

fix

Use `from esda import Moran_Local` instead of `from esda.moran import Moran_Local`.

ValueError: The weights matrix is not row-standardized.

Moran class expects row-standardized weights by default.

fix

Use `w.transform = 'R'` before passing to Moran, or create weights with row-standardization (e.g., `libpysal.weights.KNN(..., transform='R')`).

AttributeError: 'Moran' object has no attribute 'I'

The object was not created correctly; perhaps `y` is not numeric or `w` is invalid.

fix

Ensure `y` is a 1D numeric array and `w` is a properly initialized libpysal weights object.

Upgrade

Version history

2.9.0latest on PyPI · released Mar 20, 2026

Audit

Dependencies

libpysalrequiredProvides spatial weights (W) and core spatial data structures.

scipyrequiredUsed for statistical distributions and randomizations.

numpyrequiredCore array operations.

shapelyoptionalRequired for geometric operations in shape and map_comparison modules.

pandasoptionalUsed for data handling in some utilities.

Agent activity

4 hits · last 30 days

node

Resources

githubhttps://github.com/pysal/esda ↗

packagehttps://pypi.org/project/esda/ ↗

homepagehttps://pysal.org/esda/ ↗