Candidates behind each bin

Open data, curated by Claude, not validated. This dataset is open. It was assembled and matched by Claude (an AI assistant) and has not been independently validated against the FEC or HRC sources. Verify before relying on it. See Methodology.

Choose a PAC, an office and a score bin to see the candidates who received its direct contributions. Sort by clicking a column heading, or type in the search box.

rowsData = rows
viewof pacSel = Inputs.select([...new Set(pacs)], {label: "PAC", value: "Google"})
viewof officeSel = Inputs.select(["All offices", "House", "Senate"], {label: "Office", value: "All offices"})
viewof binSel = Inputs.select(["All bins", ...bins], {label: "HRC score bin", value: "All bins"})

filtered = rowsData.filter(d => d.pac === pacSel
  && (officeSel === "All offices" || d.race === officeSel)
  && (binSel === "All bins" || d.score_bin === binSel))
viewof found = Inputs.search(filtered, {placeholder: "Search candidates"})

filtered.length === 0
  ? html`<p class="note-box">No direct candidate contributions from ${pacSel} for this office and bin.</p>`
  : Inputs.table(found, {
      columns: ["candidate", "party", "state", "race", "score", "score_bin", "2024", "2026", "total"],
      header: {candidate: "Candidate", party: "Party", state: "State", race: "Office", score: "HRC score",
               score_bin: "Bin", "2024": "2024 cycle", "2026": "2026 cycle", total: "Total"},
      format: {"2024": d => d3.format("$,.0f")(d), "2026": d => d3.format("$,.0f")(d),
               total: d => d3.format("$,.0f")(d), score: d => d == null ? "n/a" : d},
      sort: "total", reverse: true, rows: 25
    })

Office is the race the contribution was made for; a candidate who ran for both chambers can appear twice. Dollars are net of refunds and voided contributions. Open data curated by Claude; not validated. HRC score is the 118th Congress score of the matched scorecard entry; candidates with no match or no score are in No score.