Public API and example inventory¶
This file is generated. Do not edit it manually.
| Namespace | Symbol | Kind | Purpose | Runnable example |
|---|---|---|---|---|
pygwrx.models |
GWR |
class | Gaussian geographically weighted regression. | examples/models/01_gwr.py |
pygwrx.models |
GWRPredictionResult |
class | Rich prediction result returned by :meth:GWR.predict_result. |
examples/models/01_gwr.py |
pygwrx.models |
MGWR |
class | Gaussian multiscale geographically weighted regression. | examples/models/02_mgwr.py |
pygwrx.models |
RGWR |
class | Classical robust geographically weighted regression. | examples/models/03_rgwr.py |
pygwrx.models |
STWR |
class | Spatiotemporal weighted regression. | examples/models/04_stwr.py |
pygwrx.models |
STWRPredictionResult |
class | Detailed predictions produced at the latest modeled time stage. | examples/models/04_stwr.py |
pygwrx.models |
GTWR |
class | Geographically and temporally weighted regression. | examples/models/05_gtwr.py |
pygwrx.models |
GTWRPredictionResult |
class | Rich prediction result returned by :meth:GTWR.predict_result. |
examples/models/05_gtwr.py |
pygwrx.models |
GWGLM |
class | Geographically weighted generalized linear model. | examples/models/06_gwglm.py |
pygwrx.models |
GWGLMPredictionResult |
class | Rich prediction result returned by :meth:GWGLM.predict_result. |
examples/models/06_gwglm.py |
pygwrx.models |
GWLasso |
class | Geographically weighted Lasso regression. | examples/models/07_gw_lasso.py |
pygwrx.models |
MixedGWR |
class | Fit a semiparametric GWR with global and local coefficients. | examples/models/08_mixed_gwr.py |
pygwrx.models |
GWPCA |
class | Fit a basic geographically weighted principal component analysis. | examples/models/09_gwpca.py |
pygwrx.models |
GWDA |
class | Fit geographically weighted linear or quadratic discriminant analysis. | examples/models/10_gwda.py |
pygwrx.models |
GWSS |
class | Compute geographically weighted summary statistics. | examples/models/11_gwss.py |
pygwrx.models |
ScalableGWR |
class | Scalable GWR using a linear multiscale polynomial kernel. | examples/models/12_scalable_gwr.py |
pygwrx.models |
LCRGWR |
class | Locally compensated ridge geographically weighted regression. | examples/models/13_lcr_gwr.py |
pygwrx.models |
BootstrapGWR |
class | Test GWR coefficient non-stationarity by parametric bootstrap. | examples/models/14_bootstrap_gwr.py |
pygwrx.models |
SGWR |
class | Similarity and geographically weighted regression. | examples/models/15_sgwr.py |
pygwrx.models |
SGTWR |
class | Spatiotemporal geographically weighted regression with similarity. | examples/models/16_sgtwr.py |
pygwrx.models |
SGTWRPredictionResult |
class | Detailed predictions from a fitted SGTWR model. | examples/models/16_sgtwr.py |
pygwrx.models |
MGTWR |
class | Gaussian multiscale geographically and temporally weighted regression. | examples/models/17_mgtwr.py |
pygwrx.models |
LGGWR |
class | Latent-Geometry Geographically Weighted Regression. | examples/models/18_lg_gwr.py |
pygwrx.models |
LGGWRPredictionResult |
class | Detailed LG-GWR predictions at evaluation locations. | examples/models/18_lg_gwr.py |
pygwrx.models |
GRGWR |
class | Geo-Regime Geographically Weighted Regression. | examples/models/19_gr_gwr.py |
pygwrx.models |
GRGWRPredictionResult |
class | Detailed GR-GWR predictions at evaluation locations. | examples/models/19_gr_gwr.py |
pygwrx.core |
BaseSpatialEstimator |
class | Root class for all spatial estimators. | examples/core/08_base_classes.py |
pygwrx.core |
BaseSpatialRegressor |
class | Base class for geographically weighted spatial regressors. | examples/core/08_base_classes.py |
pygwrx.core |
BaseGWR |
class | Base class for geographically weighted spatial regressors. | examples/core/08_base_classes.py |
pygwrx.core |
SpatiotemporalMixin |
class | No summary is available. | examples/core/08_base_classes.py |
pygwrx.core |
MultiscaleMixin |
class | No summary is available. | examples/core/08_base_classes.py |
pygwrx.core |
BaseSpatiotemporalRegressor |
class | Base for spatiotemporal GWR-family regressors. | examples/core/08_base_classes.py |
pygwrx.core |
BaseMultiscaleRegressor |
class | Base for one-bandwidth-per-coefficient regressors. | examples/core/08_base_classes.py |
pygwrx.core |
BaseSpatialClassifier |
class | Base class for spatial classifiers such as GWDA. | examples/core/08_base_classes.py |
pygwrx.core |
BaseSpatialTransformer |
class | Root class for all spatial estimators. | examples/core/08_base_classes.py |
pygwrx.core |
BaseSpatialStatistics |
class | Root class for all spatial estimators. | examples/core/08_base_classes.py |
pygwrx.core |
BaseSpatialInference |
class | Root class for all spatial estimators. | examples/core/08_base_classes.py |
pygwrx.core |
gaussian_kernel |
function | Compute Gaussian kernel weights. | examples/core/01_kernels.py |
pygwrx.core |
bisquare_kernel |
function | Compute bi-square (quartic) kernel weights. | examples/core/01_kernels.py |
pygwrx.core |
exponential_kernel |
function | Compute exponential kernel weights. | examples/core/01_kernels.py |
pygwrx.core |
tricube_kernel |
function | Compute tri-cube kernel weights. | examples/core/01_kernels.py |
pygwrx.core |
boxcar_kernel |
function | Compute boxcar (uniform) kernel weights. | examples/core/01_kernels.py |
pygwrx.core |
get_kernel_function |
function | Return a built-in kernel by name or validate a custom callable. | examples/core/01_kernels.py |
pygwrx.core |
BandwidthSelector |
class | Abstract base class for bandwidth selection methods. | examples/core/07_bandwidth_selectors.py |
pygwrx.core |
CrossValidationSelector |
class | Select bandwidth by strict leave-one-out squared prediction error. | examples/core/07_bandwidth_selectors.py |
pygwrx.core |
AICSelector |
class | Select bandwidth using Gaussian GWR AIC or AICc. | examples/core/07_bandwidth_selectors.py |
pygwrx.core |
BICSelector |
class | Select bandwidth using Gaussian GWR BIC. | examples/core/07_bandwidth_selectors.py |
pygwrx.core |
get_bandwidth_selector |
function | Create a bandwidth selector by method name. | examples/core/07_bandwidth_selectors.py |
pygwrx.core |
OptimizationResult |
class | Result returned by a one-dimensional optimizer. | examples/core/06_optimization.py |
pygwrx.core |
GoldenSectionSearch |
class | Golden-section search for one-dimensional minimization. | examples/core/06_optimization.py |
pygwrx.core |
BrentSearch |
class | Brent's bounded method for continuous one-dimensional minimization. | examples/core/06_optimization.py |
pygwrx.core |
weighted_least_squares |
function | Solve a weighted least-squares problem. | examples/core/04_solver.py |
pygwrx.core |
local_regression |
function | Perform local weighted regression at target locations. | examples/core/04_solver.py |
pygwrx.core |
compute_hat_matrix |
function | Compute the GWR hat matrix S such that y_hat = S @ y. |
examples/core/04_solver.py |
pygwrx.core |
adaptive_bandwidth_weights |
function | Convert an adaptive neighbour-order bandwidth into a distance scale. | examples/core/04_solver.py |
pygwrx.core |
compute_r_squared |
function | Compute the coefficient of determination, R². | examples/core/05_metrics.py |
pygwrx.core |
compute_adjusted_r_squared |
function | Compute GWR adjusted R² from residual effective degrees of freedom. | examples/core/05_metrics.py |
pygwrx.core |
compute_aic |
function | Compute Gaussian GWR AIC using trace(S) as the complexity term. | examples/core/05_metrics.py |
pygwrx.core |
compute_aicc |
function | Compute Gaussian GWR corrected AIC (AICc). Compute the corrected Akaike information criterion for Gaussian GWR. | examples/core/05_metrics.py |
pygwrx.core |
compute_bic |
function | Compute Gaussian GWR BIC using trace(S). | examples/core/05_metrics.py |
pygwrx.core |
compute_local_r_squared |
function | Compute local weighted R² values. Compute a locally weighted coefficient of determination. | examples/core/05_metrics.py |
pygwrx.core |
compute_effective_parameters |
function | Return trace(S), the first common effective-parameter convention. | examples/core/05_metrics.py |
pygwrx.core |
compute_diagnostics |
function | Compute diagnostic statistics for a Gaussian GWR-style model. | examples/core/05_metrics.py |
pygwrx.core |
compute_trace_statistics |
function | Compute trace(S) and trace(S'S) from a validated hat matrix. | examples/core/05_metrics.py |
pygwrx.core |
compute_edf |
function | Compute residual effective degrees of freedom using the GWmodel convention. | examples/core/05_metrics.py |
pygwrx.core |
compute_enp |
function | Compute the GWmodel-style effective number of parameters. Compute the effective parameter count using the GWmodel convention. | examples/core/05_metrics.py |
pygwrx.core |
euclidean_distance |
function | Compute pairwise Euclidean distances. Compute Euclidean distances between coordinate arrays. | examples/core/02_distances_and_validation.py |
pygwrx.core |
manhattan_distance |
function | Compute pairwise Manhattan (L1/city-block) distances. | examples/core/02_distances_and_validation.py |
pygwrx.core |
chebyshev_distance |
function | Compute pairwise Chebyshev (L-infinity) distances. | examples/core/02_distances_and_validation.py |
pygwrx.core |
minkowski_distance |
function | Compute pairwise Minkowski (Lp) distances. Compute Minkowski distances between coordinate arrays. | examples/core/02_distances_and_validation.py |
pygwrx.core |
haversine_distance |
function | Compute great-circle distances using the Haversine formula. | examples/core/02_distances_and_validation.py |
pygwrx.core |
compute_distance_matrix |
function | Compute a pairwise distance matrix. | examples/core/02_distances_and_validation.py |
pygwrx.core |
DistanceCache |
class | Distance-matrix cache policy based on actual matrix memory. Decide whether a distance matrix is small enough to cache. | examples/core/02_distances_and_validation.py |
pygwrx.core |
validate_coords |
function | Validate coordinate data and return a floating-point array of shape (n, 2). | examples/core/02_distances_and_validation.py |
pygwrx.core |
validate_data |
function | Validate a single-response feature matrix and target vector. | examples/core/02_distances_and_validation.py |
pygwrx.core |
add_intercept |
function | Add a leading intercept column of ones to a feature matrix. | examples/core/02_distances_and_validation.py |
pygwrx.core |
extract_geopandas_coords |
function | Extract [x, y] coordinates from the active Point geometry column. | examples/core/03_geopandas_coordinates.py |
pygwrx.core |
chunked_computation |
function | Yield half-open (start, end) index ranges for chunked processing. |
examples/core/02_distances_and_validation.py |
pygwrx.diagnostics |
DiagnosticSummary |
class | Normalized global diagnostics for one fitted estimator. | examples/diagnostics/01_model_and_residual_diagnostics.py |
pygwrx.diagnostics |
diagnostics_frame |
function | Return one row of normalized global diagnostics per model. | examples/diagnostics/01_model_and_residual_diagnostics.py |
pygwrx.diagnostics |
model_diagnostic_summary |
function | Normalize global diagnostics exposed by any supported fitted model. | examples/diagnostics/01_model_and_residual_diagnostics.py |
pygwrx.diagnostics |
InfluenceThresholds |
class | Common reference thresholds for local influence diagnostics. | examples/diagnostics/01_model_and_residual_diagnostics.py |
pygwrx.diagnostics |
influence_thresholds |
function | Return transparent rule-of-thumb thresholds for a fitted model. | examples/diagnostics/01_model_and_residual_diagnostics.py |
pygwrx.diagnostics |
local_diagnostic_frame |
function | Collect available row-wise diagnostics without mutating the model. | examples/diagnostics/01_model_and_residual_diagnostics.py |
pygwrx.diagnostics |
LocalCollinearityDiagnostics |
class | Diagnose spatially varying multicollinearity in a fitted GWR model. | examples/diagnostics/02_inference_and_collinearity.py |
pygwrx.diagnostics |
ParameterInference |
class | One local coefficient surface with inference arrays. | examples/diagnostics/02_inference_and_collinearity.py |
pygwrx.diagnostics |
adjust_pvalues |
function | Adjust p values using Bonferroni, BH, or BY correction. | examples/diagnostics/02_inference_and_collinearity.py |
pygwrx.diagnostics |
feature_names |
function | Return stable predictor names for a fitted model. | examples/diagnostics/02_inference_and_collinearity.py |
pygwrx.diagnostics |
parameter_inference |
function | Extract a coefficient, test statistic, and standard error surface. | examples/diagnostics/02_inference_and_collinearity.py |
pygwrx.diagnostics |
parameter_significance |
function | Return coefficient values, p values, and significance categories. | examples/diagnostics/02_inference_and_collinearity.py |
pygwrx.diagnostics |
TemporalGroups |
class | Unique time values and row indices for a fitted spatiotemporal model. | examples/diagnostics/03_temporal_diagnostics.py |
pygwrx.diagnostics |
model_times |
function | Return one time value per plotted row. | examples/diagnostics/03_temporal_diagnostics.py |
pygwrx.diagnostics |
parameter_trajectory |
function | Aggregate a parameter surface over time or follow the nearest location. | examples/diagnostics/03_temporal_diagnostics.py |
pygwrx.diagnostics |
temporal_groups |
function | Group fitted rows by exact time value while preserving chronological order. | examples/diagnostics/03_temporal_diagnostics.py |
pygwrx.diagnostics |
temporal_parameter_frame |
function | Return local parameters with coordinates and times in tidy form. | examples/diagnostics/03_temporal_diagnostics.py |
pygwrx.diagnostics |
WeightComponents |
class | Named weight matrices exposed by a fitted model. | examples/diagnostics/04_weight_diagnostics.py |
pygwrx.diagnostics |
focus_weight_components |
function | Return one row from every stored weight component. | examples/diagnostics/04_weight_diagnostics.py |
pygwrx.diagnostics |
weight_components |
function | Collect stored weight matrices using stable semantic names. | examples/diagnostics/04_weight_diagnostics.py |
pygwrx.diagnostics |
boundary_frame |
function | Return unique regime-boundary edges and their endpoints. | examples/diagnostics/05_regime_diagnostics.py |
pygwrx.diagnostics |
regime_frame |
function | Return coordinates, regime labels, residuals, and connectivity metadata. | examples/diagnostics/05_regime_diagnostics.py |
pygwrx.diagnostics |
regime_summary |
function | Summarize regime sizes, residual error, and component counts. | examples/diagnostics/05_regime_diagnostics.py |
pygwrx.plotting |
plot_coefficient_map |
function | Plot one fitted local coefficient surface. | examples/plotting/01_surfaces_and_arrays.py |
pygwrx.plotting |
plot_significance_map |
function | Dispatch to model-aware or historical array-based significance mapping. | examples/plotting/01_surfaces_and_arrays.py |
pygwrx.plotting |
plot_model_significance_map |
function | Map negative-significant, non-significant, and positive-significant areas. | examples/plotting/01_surfaces_and_arrays.py |
pygwrx.plotting |
plot_local_diagnostic_map |
function | Plot a fitted local diagnostic such as Local R² or Cook's distance. | examples/plotting/01_surfaces_and_arrays.py |
pygwrx.plotting |
plot_local_collinearity |
function | Plot local condition numbers or LCR-GWR ridge compensation. | examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
plot_array_significance_map |
function | Plot significant and non-significant locations from local p-values. | examples/plotting/01_surfaces_and_arrays.py |
pygwrx.plotting |
plot_local_coefficients |
function | Plot one column of a local coefficient array. | examples/plotting/01_surfaces_and_arrays.py |
pygwrx.plotting |
plot_coefficient_surface |
function | Interpolate a local coefficient array to a regular plotting grid. | examples/plotting/01_surfaces_and_arrays.py |
pygwrx.plotting |
plot_local_r2 |
function | Plot spatial local R² values. | examples/plotting/01_surfaces_and_arrays.py |
pygwrx.plotting |
plot_bandwidth |
function | Visualize fixed-distance bandwidth footprints at selected locations. | examples/plotting/01_surfaces_and_arrays.py |
pygwrx.plotting |
create_choropleth |
function | Create a validated GeoDataFrame choropleth. | examples/plotting/01_surfaces_and_arrays.py |
pygwrx.plotting |
plot_multiple_coefficients |
function | Create a panel containing every coefficient column. | examples/plotting/01_surfaces_and_arrays.py |
pygwrx.plotting |
compare_coefficient_surfaces |
function | Compare the same local coefficient across two or more fitted models. | examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
compare_model_diagnostics |
function | Compare normalized global diagnostics across fitted models. | examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
plot_kernel_weights |
function | Show the spatial neighbourhood and weight-decay curve at one calibration point. | examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
plot_mgwr_bandwidths |
function | Plot variable-specific MGWR bandwidths. | examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
plot_residuals |
function | Plot residuals against fitted values with a binned mean trend. | examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
plot_residual_histogram |
function | Plot a residual histogram and optional fitted normal density. | examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
plot_qq |
function | Create a normal Q–Q plot for residuals. | examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
plot_spatial_residuals |
function | Map residuals using calibration point coordinates. | examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
plot_observed_vs_predicted |
function | Plot observed and predicted values with a one-to-one reference. | examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
plot_bandwidth_selection |
function | Compatibility wrapper for :func:pygwrx.plotting.bandwidth.plot_bandwidth_selection. |
examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
plot_coefficient_variability |
function | Compare distributions of local coefficients across variables. | examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
plot_diagnostic_panel |
function | Create a complete calibration-diagnostic panel without displaying it. | examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
plot_local_diagnostics |
function | Plot several local diagnostic arrays on a common coordinate set. | examples/plotting/02_diagnostics_and_comparison.py |
pygwrx.plotting |
plot_rgwr_weights |
function | Map final robust weights and outline completely rejected observations. | examples/plotting/03_robust_regularized_bootstrap.py |
pygwrx.plotting |
plot_rgwr_convergence |
function | Plot iteration MSE and the number of downweighted observations. | examples/plotting/03_robust_regularized_bootstrap.py |
pygwrx.plotting |
plot_gwglm_residuals |
function | Map Pearson, deviance, or raw residuals from a fitted GWGLM. | examples/plotting/03_robust_regularized_bootstrap.py |
pygwrx.plotting |
plot_gwlasso_selection_frequency |
function | Plot the percentage of locations with a non-zero coefficient. | examples/plotting/03_robust_regularized_bootstrap.py |
pygwrx.plotting |
plot_gwlasso_active_map |
function | Map locations where a GWLasso coefficient is active. | examples/plotting/03_robust_regularized_bootstrap.py |
pygwrx.plotting |
plot_gwlasso_alpha |
function | Map the locally selected Lasso penalty. | examples/plotting/03_robust_regularized_bootstrap.py |
pygwrx.plotting |
plot_mixed_gwr_coefficients |
function | Compare global coefficients with distributions of local coefficients. | examples/plotting/03_robust_regularized_bootstrap.py |
pygwrx.plotting |
plot_bootstrap_pvalues |
function | Map localized bootstrap p values or show a global modified-test p value. | examples/plotting/03_robust_regularized_bootstrap.py |
pygwrx.plotting |
plot_bootstrap_bandwidths |
function | Plot bandwidth variability across bootstrap replications. | examples/plotting/03_robust_regularized_bootstrap.py |
pygwrx.plotting |
plot_gwss_statistic |
function | Map a local GWSS univariate or pairwise summary statistic. | examples/plotting/04_multivariate_and_classification.py |
pygwrx.plotting |
plot_gwpca_explained_variance |
function | Map local explained variance for one component or cumulatively. | examples/plotting/04_multivariate_and_classification.py |
pygwrx.plotting |
plot_gwpca_loading |
function | Map a local principal-component loading surface. | examples/plotting/04_multivariate_and_classification.py |
pygwrx.plotting |
plot_gwda_classification |
function | Map predicted classes or maximum class probability for GWDA. | examples/plotting/04_multivariate_and_classification.py |
pygwrx.plotting |
plot_gwda_confusion_matrix |
function | Plot a calibration/validation confusion matrix when labels are available. | examples/plotting/04_multivariate_and_classification.py |
pygwrx.plotting |
plot_scalable_gwr_kernel |
function | Plot fitted polynomial-kernel components and their mixture. | examples/plotting/03_robust_regularized_bootstrap.py |
pygwrx.plotting |
plot_temporal_coefficient_slices |
function | Plot coefficient maps at selected observed time slices. | examples/plotting/05_temporal_and_weights.py |
pygwrx.plotting |
plot_mgtwr_scales |
function | Plot variable-specific spatial bandwidths and temporal scale parameters. | examples/plotting/05_temporal_and_weights.py |
pygwrx.plotting |
plot_temporal_trajectory |
function | Plot a coefficient trajectory aggregated by time or followed by location. | examples/plotting/05_temporal_and_weights.py |
pygwrx.plotting |
plot_temporal_residuals |
function | Plot fitted residuals against time with a zero reference line. | examples/plotting/05_temporal_and_weights.py |
pygwrx.plotting |
plot_temporal_bandwidths |
function | Plot spatial/temporal scales for GTWR, MGTWR, STWR, or SGTWR. | examples/plotting/05_temporal_and_weights.py |
pygwrx.plotting |
plot_weight_decomposition |
function | Map stored spatial, temporal, similarity, and combined weights. | examples/plotting/05_temporal_and_weights.py |
pygwrx.plotting |
plot_weight_profiles |
function | Compare sorted one-dimensional profiles of stored weight components. | examples/plotting/05_temporal_and_weights.py |
pygwrx.plotting |
plot_selection_history |
function | Plot AICc/CV values from an SGWR/STWR/SGTWR parameter search. | examples/plotting/05_temporal_and_weights.py |
pygwrx.plotting |
plot_lggwr_latent_geometry |
function | Compare physical coordinates with the first two latent dimensions. | examples/plotting/06_lggwr_and_grgwr.py |
pygwrx.plotting |
plot_lggwr_metric_matrix |
function | Plot the rotation-invariant metric matrix A.T @ A or B.T @ B. |
examples/plotting/06_lggwr_and_grgwr.py |
pygwrx.plotting |
plot_lggwr_training |
function | Plot LOO loss and bandwidth updates from latent-geometry learning. | examples/plotting/06_lggwr_and_grgwr.py |
pygwrx.plotting |
plot_lggwr_neighbourhood_comparison |
function | Compare geographical and learned nearest neighbours around one observation. | examples/plotting/06_lggwr_and_grgwr.py |
pygwrx.plotting |
plot_grgwr_regimes |
function | Map final mechanism regimes and optional boundary graph edges. | examples/plotting/06_lggwr_and_grgwr.py |
pygwrx.plotting |
plot_grgwr_convergence |
function | Plot the accepted penalized objective sequence. | examples/plotting/06_lggwr_and_grgwr.py |
pygwrx.plotting |
plot_grgwr_regime_sizes |
function | Plot sample counts and optional RMSE by final regime. | examples/plotting/06_lggwr_and_grgwr.py |
pygwrx.plotting |
plot_grgwr_coefficient_surface |
function | Map a GR-GWR coefficient while overlaying discovered regime boundaries. | examples/plotting/06_lggwr_and_grgwr.py |
pygwrx.io |
load_data |
function | Load a user data file and extract model features, target, and coordinates. Extract predictors, an optional response, and coordinates from a user data file. | examples/io/02_tabular_roundtrip.py |
pygwrx.io |
to_geodataframe |
function | Convert aligned arrays into a point GeoDataFrame. | examples/io/03_geodataframe_roundtrip.py |
pygwrx.io |
from_geodataframe |
function | Extract aligned arrays from a point GeoDataFrame. | examples/io/03_geodataframe_roundtrip.py |
pygwrx.io |
save_results |
function | Save model results to CSV, Parquet, Shapefile, GeoJSON, or GeoPackage. | examples/io/02_tabular_roundtrip.py |
pygwrx.io |
load_dataset |
function | Load a bundled example dataset by name. | examples/io/01_bundled_datasets.py |
pygwrx.io |
load_dublin_voter |
function | Load the Dublin voter turnout dataset. See :func:load_dataset. |
examples/io/01_bundled_datasets.py |
pygwrx.io |
load_hiv |
function | Load the county-level HIV prevalence dataset. See :func:load_dataset. |
examples/io/01_bundled_datasets.py |
pygwrx.io |
load_crime |
function | Load the county-level crime dataset. See :func:load_dataset. |
examples/io/01_bundled_datasets.py |
pygwrx.io |
load_housing |
function | Load the neighborhood house-price dataset. See :func:load_dataset. |
examples/io/01_bundled_datasets.py |
pygwrx.io |
load_columbus |
function | Load the Columbus (OH) crime dataset. See :func:load_dataset. |
examples/io/01_bundled_datasets.py |
pygwrx.io |
load_ewhp |
function | Load the England & Wales house-price dataset. See :func:load_dataset. |
examples/io/01_bundled_datasets.py |
pygwrx.io |
load_georgia |
function | Load the Georgia educational-attainment dataset. See :func:load_dataset. |
examples/io/01_bundled_datasets.py |
pygwrx.io |
get_dublin_voter |
function | Load the Dublin voter turnout dataset. See :func:load_dataset. |
examples/io/01_bundled_datasets.py |
pygwrx.io |
load_dubvoter |
function | Load the Dublin voter turnout dataset. See :func:load_dataset. |
examples/io/01_bundled_datasets.py |
pygwrx.io |
get_dubvoter |
function | Load the Dublin voter turnout dataset. See :func:load_dataset. |
examples/io/01_bundled_datasets.py |
pygwrx.io |
get_dataset_info |
function | Return registry metadata for a dataset without loading its data file. | examples/io/01_bundled_datasets.py |
pygwrx.io |
list_datasets |
function | List available built-in datasets and optionally print their metadata. | examples/io/01_bundled_datasets.py |