Study 01: Intro to MESQUAL¶
The intro study primarily uses a PyPSA example network to introduce the MESQUAL modules and framework. The series is structured as follows and will continuously be updated. So stay tuned.
Getting Started Series¶
- mesqual_101_study_manager_and_basic_fetching - Getting started with scenarios and comparisons
- mesqual_102_mastering_data_fetching - Mastering the fetch method and data access patterns
- mesqual_103_scenario_attributes - Managing and utilizing scenario metadata effectively
KPI Framework Series¶
- mesqual_201_kpi_framework_and_units - Building a structured KPI system with proper unit handling
- mesqual_202_kpi_collections_and_tables - Extracting pretty KPI tables
Visualization Series¶
- mesqual_301_time_series_dashboard - The best way to visualize, compare and understand time-series
- mesqual_302_segmented_colormap - A useful colormap to merge multiple linear segments into a single colormap
- mesqual_303_folium_model_df_map - Creating interactive Folium maps visualizing model info
- mesqual_304_folium_area_kpi_map - Creating interactive Folium maps with area KPIs for scenarios and comparisons
- mesqual_305_area_border_kpi_map - Creating interactive Folium maps with area-border KPIs for scenarios and comparisons
- mesqual_306_icon_kpi_map - Creating interactive Folium maps with KPIs projected as icons for scenarios and comparisons
- mesqual_307_country_plotter_util - GeoJSON library of country shapes
- mesqual_308_html_dashboards - Multiple HTML plots (e.g. plotly figures) in one share-able html file
Advanced Dataset Handling Series¶
- mesqual_401_dataset_collections - Linking, merging and managing multiple data sources
- mesqual_402_custom_interpreters - Creating study-specific data interpreters and variables
- mesqual_403_model_timeseries_integration - Combining static model data with time series for richer analysis
- mesqual_404_dot_notation_api - Using Python's dot notation for elegant data access
Expert Dataset Handling Series¶
- mesqual_501_configuration_hierarchy - Mastering dataset and fetch-level configurations
- mesqual_502_validation_framework - Ensuring data consistency across scenarios
- mesqual_503_pickle_database_integration - Intro to simple .pickle DB integration for faster fetching
Managing Multiple Studies Series¶
- mesqual_601_multi_study_architecture - Organizing repositories with multiple studies
- mesqual_602_color_themes - Managing different color themes across different studies
Interface Builder Series¶
- mesqual_701_platform_dataset - An abstract container class for data interpreters to cover all aspects of handling data from a platform
- mesqual_702_flag_index_system - Understanding relationships between model and time series data
- mesqual_703_model_enrichment_patterns - Advanced techniques for property and membership enrichment
- mesqual_704_variable_aggregation_patterns - Advanced techniques for automatic variable aggregations
Advanced DataFrame Handling Series¶
- mesqual_801_granularity_analysis_and_conversion - Handling time-series of different granularities
- mesqual_802_multi_index_utils - xs_df, set_new_column, sort_multi_index
References and Third-Party Assets¶
- PyPSA and Scigrid-DE example network:
- [MIT License] - GeoJSON of DE control areas:
- [CC BY 4.0]