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Dataframe to Dict

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)

Dataframe to Dict has 2 facts recorded in Dontopedia across 1 reference.

2 facts·2 predicates·1 sources
Maturity scale raw canonical shape-checked rule-derived certified

Orientationorientation

  • records[1]sourceall time · 92f9d4b6 659a 439c Ae2a 0330d3d8ab30

Methodmethod

  • to_dict[1]sourceall time · 92f9d4b6 659a 439c Ae2a 0330d3d8ab30

Inbound mentions (2)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

convertsConverts(1)

usesUses(1)

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

2 undated
—
methodbeam/92f9d4b6-659a-439c-ae2a-0330d3d8ab30
to_dict
—
orientationbeam/92f9d4b6-659a-439c-ae2a-0330d3d8ab30
records

References (1)

1 references
  1. [1]beam-chunk2 facts
    customctx:claims/beam/92f9d4b6-659a-439c-ae2a-0330d3d8ab30
    • full textbeam-chunk
      text/plain1 KBdoc:beam/92f9d4b6-659a-439c-ae2a-0330d3d8ab30
      Show excerpt
      'vector': [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6], [0.7, 0.8, 0.9]] } # Create a DataFrame to store the data df = pd.DataFrame(data) # Connect to MongoDB client = MongoClient('mongodb://localhost:27017/') db = client['rag_db'] collection = …

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