Projects sharing features with Pysal

Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management. It utilizes a Cypher query engine for declarative data retrieval and manipulation, providing a scalable knowledge graph backend that integrates vector search and graph traversals. The system distinguishes itself as a real-time graph analytics platform, employing native C++ and CUDA implementations to execute complex network analysis and dynamic community detection on streaming data. It provides specialized support for AI integration, including GraphRAG capabilities, the constr

SpatialLM is a spatial modeling framework that uses large language models to transform monocular video and sensor data into structured indoor semantic maps. It functions as a system for indoor layout estimation and a point cloud semantic parser, converting raw geometric data into representations of architectural elements and object categories. The project aligns multi-modal sensor inputs with linguistic tokens, allowing a language model to serve as a reasoning engine for inferring room topology. It employs mechanisms to convert 3D point clouds and 2D image sequences into discrete tokens and s

This repository is a collection of practical machine learning implementations designed to demonstrate core predictive analytics, computer vision, and natural language processing techniques. It serves as a resource for applying standard machine learning frameworks to solve diverse data science problems, ranging from automated classification to complex pattern recognition. The project distinguishes itself by providing concrete examples across multiple domains, including the development of conversational interfaces, the analysis of geospatial data, and the implementation of deep learning archite

Classes and methods for spatio-temporal data

Documentation and samples for ArcGIS API for Python

geopy is a Python geocoding library and geolocation client used to convert human-readable addresses into geographic coordinates and resolve coordinates back into street addresses using various third-party web services. The library provides a consistent provider-based interface that abstracts multiple external geocoding services, allowing for interchangeable backends. It includes built-in request rate limiting and asynchronous client interfaces to manage API call frequency and execute concurrent lookups without halting execution. Beyond geocoding, the project includes geospatial utilities for

pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef enu eci

The igraph library

Website:

Beautiful visualizations of how language differs among document types.

Python bindings and utilities for GeoJSON

Text preprocessing, representation and visualization from zero to hero.

Joblib is a suite of utilities for parallelizing computational workloads and optimizing the storage of large numerical datasets and function results. It functions as a parallel computing library and multiprocessing wrapper that distributes function execution across multiple CPU cores to accelerate independent tasks and computational loops. The project provides a disk caching framework that persists expensive function outputs to the filesystem, re-evaluating them only when input arguments change. It further specializes in the serialization of large numerical arrays, utilizing efficient compres

Faker is a Python library designed to generate realistic synthetic data for software testing, database prototyping, and privacy-preserving anonymization. It provides a comprehensive suite of tools to create diverse information types, including personal identities, financial records, geographic locations, and technical system metadata, allowing developers to populate environments with mock data that mimics real-world structures. The library is built on a modular provider architecture that supports dynamic method dispatch, enabling users to extend functionality by registering custom data genera

A Jupyter - Leaflet.js bridge

create a map by R

Mimesis is a Python synthetic data generator used to create realistic fake datasets and mock data for software testing and development. It functions as a schema-based dataset generator capable of producing structured records and relational datasets, while also serving as a production data anonymizer to replace sensitive information with synthetic values. The library distinguishes itself through comprehensive multilingual support, allowing for the generation of locale-specific information to simulate regional user profiles. It ensures reproducibility through deterministic data generation using

Use Mapbox GL JS to visualize data in a Python Jupyter notebook

R package for thematic maps

NetworkX is a Python library designed for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. It provides a comprehensive framework for modeling relationships between entities as graphs, directed graphs, or multigraphs, allowing users to attach arbitrary metadata and properties to nodes and edges. The library distinguishes itself through a modular architecture that decouples graph analysis logic from data storage, utilizing nested dictionaries and adjacency lists to manage topology. It features a pluggable backend system that delegates computat

cuDF is a GPU-accelerated dataframe library and data processing engine designed for manipulating and analyzing large tabular datasets. It provides a high-level API for executing filtering, joining, and aggregating operations directly on GPU hardware. The project integrates the Apache Arrow memory format to enable zero-copy data transfers and includes a just-in-time compiler for executing custom user-defined functions on the GPU. The library features specialized acceleration for existing workflows by redirecting standard Pandas dataframe calls and Polars query plans to a GPU backend. It also p

Rasterio reads and writes geospatial raster datasets

Shapely is a library for the manipulation and analysis of planar geometric objects, serving as a Python wrapper for the GEOS C++ engine. It provides a framework for calculating geometric properties, evaluating spatial relationships, and performing topological predicates within a Cartesian plane. The project distinguishes itself through a vectorized geometry processor capable of executing spatial operations across large arrays of shapes to increase throughput. It also includes a spatial indexing system based on R-trees to accelerate the retrieval of intersecting geometries and nearest neighbor