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name: entitysets-and-data description: "Create, inspect, normalize, serialize, and query Featuretools EntitySets and built-in demo datasets." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

EntitySets And Data

Use this sub-skill when the task is about the raw data model that feeds Featuretools: building an EntitySet, adding relationships, setting time indexes, querying rows, loading demo datasets, or serializing entity graphs.

Route Here For

• Creating an EntitySet from one or more pandas dataframes.
• Adding relationships, normalizing child tables, or changing time-index metadata.
• Inspecting paths, query results, or the entity graph structure.
• Loading the built-in demo datasets and deciding which ones are safe offline.
• Saving or reloading an entity graph with to_pickle, to_csv, read_entityset, or optional to_parquet.
• Debugging Graphviz, parquet, index, and time-type issues around data setup.

Start With These References

• ../../references/api-reference.md: the EntitySet, Relationship, Timedelta, demo-loader, and serialization signatures.
• references/workflows.md: a step-by-step EntitySet setup and demo-data workflow.
• references/troubleshooting.md: graph rendering, parquet, network-loader, and time-index recovery notes.
• scripts/entityset_smoke.py: a tiny self-check that builds and reloads a small entity graph.

Boundaries

• Stay inside raw data modeling, path inspection, and serialization.
• Route DFS, feature matrices, cutoffs, and encode_features to ../deep-feature-synthesis/.
• Route primitive discovery, feature selection, and package info to ../feature-inspection-and-selection/.
• Route custom primitive authoring, describe_feature, graph_feature, and feature-definition persistence to ../primitives-and-feature-definitions/.

Minimal Workflow

1. Start with load_mock_customer(return_entityset=True) if you only need a safe demo dataset.
2. Add your own dataframes with add_dataframe or normalize_dataframe.
3. Add relationships and time metadata before generating features.
4. Use query_by_values, find_forward_paths, and get_backward_dataframes to inspect the graph.
5. Save the entity graph with to_pickle or to_csv; use to_parquet only when pyarrow is installed.

Common Decision Points

• Use set_secondary_time_index only when the extra time column shares the entityset time type.
• Use make_index=True or a true index column before normalization if the source dataframe has no natural key.
• Treat plot as optional; it is only worth attempting when Graphviz is already installed.
• Treat load_retail, load_flight, and load_weather as optional or network-backed workflows.

Quality Bar

Future agents should be able to create a working EntitySet and recover it from disk without reopening the original repository.