Spatio-Temporal Discretizator for spatio-Temporal data wrangling and analysis. If you have data from events with geographical and temporal information and want to create analytical datasets aggregating this information with other sources, spated can help you.
Just run python -m pip install spated.
Use DataAggregator object to merge information from your multiple datasources.
import spated
app = spated.DataAggregator()
# add your events dataset
# for example, a dataset with ambulance calls registers
app.add_events(ambulance_calls_df)
# add a base geographical limit as a geopandas.GeoDataFrame to locate the analysis
app.add_max_borders(base_map)
# you can also estimate a base map from our implemented methods
# app.add_max_borders(method='convex')
# compute time indexes from events
# for example, a 4-hour window daily sazonality
app.add_time_discretization(sazonality_type='H', window=4, frequency=24)
# compute geographical discretization
# for example, split your map into rectangles with 15 horizontal splits and 20 vertical splits
app.add_geo_discretization(discr_type='R', rect_discr_param_x=15, rect_discr_param_y=20)
# and finally, add more information from other geo-located data sources
# for example, the population from neighborhoods of original map
app.add_geo_features(neighborhoods_population)For more details and options, check usage_example.ipynb notebook.