Maskína — Public Opinion Polls

Public opinion polls and surveys from Iceland's leading polling company. Two data sources: WordPress articles (prose) and Tableau Public dashboard (structured).

This is the first stop for opinion-poll questions. The data here comes structured, straight from the pollster — no browser, no news-article scraping. Only when the question needs other pollsters (Gallup, Prósent, Félagsvísindastofnun), cross-pollster comparison, or polls Maskína never published itself should you fall back to the heavier skodanakannanir skill (number extraction from RÚV/Vísir/Heimildin news articles).

Data Sources

1. WordPress REST API (articles)

Base URL: https://maskina.is/wp-json/wp/v2/posts

Open API, no authentication. Standard WP REST endpoints.

# Latest posts
curl 'https://maskina.is/wp-json/wp/v2/posts?per_page=5&orderby=date&order=desc&_fields=id,title,date,link,excerpt'

# Search for party support polls
curl 'https://maskina.is/wp-json/wp/v2/posts?search=fylgi&per_page=5&_fields=id,title,date,link,excerpt'

# Full article by ID
curl 'https://maskina.is/wp-json/wp/v2/posts/6412?_fields=id,title,date,link,content'

Content format: HTML in content.rendered. Requires HTML stripping. Poll data is embedded as prose text — "Samfylkingin stendur nú í um 25% fylgi".

Search is a full-text index, not a fixed set of topics. /wp/v2/categories returns only Fréttir (339 posts) and Uncategorized @is (32) — there is no real taxonomy to browse. /wp/v2/tags is empty. The ?search= parameter is the only practical way to find topical content, and it matches title + body text freely — any word Maskína has ever polled about works, not just the terms below.

Known recurring, branded series (repeated release after release — worth building a systematic fetcher around, the way fylgi already is):

Series	Search term(s)	Example title
Fylgi flokka (national party support)	fylgi	"Ný fylgismæling fyrir flokka á Alþingi"
Borgarviti (Reykjavík city politics)	borgarviti	"Borgarviti Maskínu: vaxandi óánægja með störf borgarstjóra"
Stofnanaviti (institutional trust)	stofnanaviti	"Stofnanaviti Maskínu er kominn út!"
ESB/aðild (EU membership)	ESB, aðild, Evrópusambandið	"53% hlynnt áframhaldandi aðildarviðræðum við ESB" (2026-01-12)
Traust til ráðherra/ríkisstjórnar (government/minister trust & approval)	ríkisstjórnin, ráðherra	"Ný traust mæling allra ráðherra"
Meðmæling Maskínu (annual "recommended companies")	Meðmæling	"12 fyrirtæki hljóta Meðmælingu Maskínu 2023"
Kryddsíld (year-end TV special poll)	Kryddsíld	"Kannanir úr Kryddsíld 2023"
Áramótaskaupið (satisfaction with the New Year's Eve comedy show)	Áramótaskaupið	"Gríðarleg ánægja með Áramótaskaupið"
Eurovision	Eurovision	"13% horfðu á Eurovision í ár"

All nine confirmed live (2026-08-01) via curl .../wp/v2/posts?search=<term> — each returns real, on-topic results, not just a single title-match fluke.

Beyond these, the archive is 371 posts deep (x-wp-total response header) and covers plenty of one-off newsworthy topics that never repeat as a named series — laxeldi (fish farming), veggjöld (road tolls), leiguþak (rent caps), flóttafólk (refugees), Borgarlína, hvalveiðar (whaling), and more. These are real and searchable, just not catalogued here individually — if asked about a topic not in the table above, search for it directly rather than assuming Maskína hasn't polled on it.

Worked example — ESB (2026-01-12, https://maskina.is/53-hlynnt-aframhaldandi-adildarvidraedum-vid-esb/): a poll originally commissioned for Sýn's Kryddsíld broadcast, published with Sýn's permission. Prose carries one clean extractable figure — "um 53% þeirra sem taka afstöðu í könnuninni eru hlynnt áframhaldandi aðildarviðræðum sem eru um 2 prósentustigum meira en þegar spurningin var borin upp ári áður" — followed by full methodology (Þjóðgátt panel, n=1,765, weighted by Þjóðskrá, fielded 3.-15. October 2025). Same shape as party-support articles: one prose sentence carries the headline number, methodology follows in the paragraphs after.

The article also embeds a Tableau viz (<div id="viz1768228030864">) distinct from the FylgiFlokka-heimasa workbook documented below — confirmed live 2026-08-01: workbook 12_01_2026-ESB_virur, view Frtt-ESB, worksheet helstu-ESB (2), readable with the exact VizQL flow below (response ~100KB, 2 chunks). It carries the referendum question ("Ef haldin verður atkvæðagreiðsla um áframhaldandi aðildarviðræður við ESB, myndir þú greiða atkvæði með eða á móti?") across two waves (2024-12-01, 2025-12-01): Með 50.9% → 53.0%, Á móti 49.1% → 47.0%, plus weighted respondent counts — matching the article's "um 2 prósentustigum meira en ári áður" exactly. Two generalizable lessons: the dated workbook name implies one-off per-article workbooks (future ESB releases will likely ship a new workbook, not update this one), and the workbook/view names are discoverable from the article HTML — grep for the static-image URL, shaped public.tableau.com/static/images/12/12_01_2026-ESB_virur/Frtt-ESB/1.png.

Caveat: broad search terms return false positives — verify each hit, don't trust title-matching alone. Pulling the 3 most recent ESB/aðild/Evrópusambandið hits live (2026-08-01) surfaced:

1. 2026-01-12 — the ESB-referendum poll above. Relevant.
2. 2022-04-04 — "Maskína gerir reglulega kannanir á Íslandi fyrir Framkvæmdastjórn Evrópusambandsins" — matched only because "Evrópusambandið"/"Evrópusvæðinu" appear often in the text. It's an EU Commission survey of European SMEs' green-market practices (89% of EU SMEs, 37% of Icelandic ones, have taken sustainability steps) — not an Icelandic membership-opinion poll at all. A naive --topic esb fetcher would misparse this as a referendum-support article and either extract garbage or (more likely, since it has no hlynnt/andvígt framing) silently produce nothing — either way, don't assume a search hit is on-topic without reading it.
3. 2021-02-06 — inngöngu-stuðningur (membership support, not just "continue negotiations"): ~30% hlynnt, ~42% andvíg, plus a party-affiliation breakdown (Viðreisn 76.9% hlynnt, Miðflokkur 75.8% andvígt, etc.) — a genuinely different question from "aðildarviðræður" in the 2026 article. Worth keeping the two framings (support continuing negotiations vs. support membership itself) distinct in any extraction logic — they are not interchangeable numbers.

2. Tableau Public Dashboard (structured data)

Dashboard: FylgiFlokka-heimasa on public.tableau.com Sheet: Nýjasta mæling (latest poll)

The dashboard provides structured party support data — percentages, month-over-month changes, and election comparison. Updated automatically when Maskína publishes a new poll.

VizQL Extraction Flow

Tableau Public uses an undocumented VizQL API. Two-step session flow:

Step 1: startSession

POST https://public.tableau.com/vizql/w/FylgiFlokka-heimasa/v/Njastamling/startSession/viewing
  ?:display_static_image=y&:bootstrapWhenNotified=true&:embed=true
  &:language=en-US&:embed=y&:showVizHome=n&:apiID=host0&:redirect=auth

Body: empty
Response: JSON with sessionid, stickySessionKey
Headers: x-session-id, global-session-header, set-cookie

Key response fields:

• sessionid — session identifier (also in x-session-id header)
• stickySessionKey — JSON string for server affinity
• global-session-header — Base64-encoded routing value (NOT the same as session ID)

Step 2: bootstrapSession

POST https://public.tableau.com/vizql/w/FylgiFlokka-heimasa/v/Njastamling
  /bootstrapSession/sessions/{sessionId}

Headers:
  Content-Type: application/x-www-form-urlencoded
  Cookie: {set-cookie values from step 1}
  global-session-header: {from step 1 response header}
  x-tsi-active-tab: N%C3%BDjasta%20m%C3%A6ling

Body (form-encoded):
  worksheetPortSize={"w":1100,"h":1800}
  dashboardPortSize={"w":1100,"h":1800}
  clientDimension={"w":1003,"h":1022}
  sheet_id=N%C3%BDjasta%20m%C3%A6ling
  stickySessionKey={from step 1 JSON}
  renderMapsClientSide=true
  isBrowserRendering=true
  browserRenderingThreshold=100
  formatDataValueLocally=false
  locale=en_US
  language=en

Response: ~650KB proprietary format (length-prefixed JSON chunks)

Parsing the Bootstrap Response

The response contains two length-prefixed JSON chunks:

590031;{...chunk 0 (layout/metadata)...}63012;{...chunk 1 (data)...}

Split on /\d+;(?=\{)/ regex. Chunk 0 (~576KB) is layout metadata — skip. Chunk 1 (~61KB) contains secondaryInfo with actual poll data.

Data dictionary path:

secondaryInfo.presModelMap.dataDictionary.presModelHolder
  .genDataDictionaryPresModel.dataSegments["0"].dataColumns

Two arrays:

• real (529 values) — percentages as fractions (0–1), bar heights, and other numerics
• cstring (93 values) — party names, dates, labels

Viz data path (column mapping):

secondaryInfo.presModelMap.vizData.presModelHolder
  .genPresModelMapPresModel.presModelMap["bar kosningar"]
  .presModelHolder.genVizDataPresModel.paneColumnsData.paneColumnsList

The bar kosningar worksheet has three columns via valueIndices:

Column	Type	Pattern	Example
Dates	cstring indices	N× per party	[11,12,14,16, 11,12,14,16, ...] → "20260601", "20260501", "20260401", "20241130"
Party names	cstring indices	N× repeated	[2,2,2,2, 3,3,3,3, ...] → "Samfylkinguna", "Sjálfstæðisflokkinn", ...
Percentages	real indices	sequential N-tuples	[36,37,38,39, 40,41,42,43, ...] → latest, previous month, month before that, election

Period count is N=4 as of 2026-07-21 (latest, previous month, month before that, last election "Kosningar '24"), NOT 3. This was originally documented as 3 — verified wrong live: naively striding by 3 through a period-4 array desyncs party names from percentages roughly every other party, producing duplicate party rows with garbage values (e.g. "Samfylkingin" appearing twice at 25.2% and 20.8%) instead of one row per party. Don't hardcode the stride — detect it live from the data instead (see _detect_stride() below): find the smallest N where party_indices is consistent in contiguous blocks of N (same party name repeats exactly N times, then changes). Verified live: for the current 9-party × 4-period = 36-length array, both N=3 and N=4 divide 36 evenly, so a "does the count divide evenly" check alone is not sufficient — cross-checking block-by-block consistency is what actually catches the 4-vs-3 case correctly.

Party Names (accusative → nominative)

Tableau uses accusative case. Map to nominative for display:

Tableau (þolfall)	Display (nefnifall)
Samfylkinguna	Samfylkingin
Miðflokkinn	Miðflokkurinn
Sjálfstæðisflokkinn	Sjálfstæðisflokkurinn
Viðreisn	Viðreisn
Framsóknarflokkinn	Framsóknarflokkurinn
Flokk fólksins	Flokkur fólksins
Pírata	Píratar
VG	Vinstrihreyfingin – grænt framboð
Sósíalistaflokkinn	Sósíalistaflokkurinn

Extraction with Python

import httpx
import re
import json

TABLEAU_BASE = "https://public.tableau.com"
WORKBOOK = "FylgiFlokka-heimasa"
SHEET = "Njastamling"
ACTIVE_TAB = "N%C3%BDjasta%20m%C3%A6ling"

PARTY_NAMES = {
    "Samfylkinguna": "Samfylkingin",
    "Miðflokkinn": "Miðflokkurinn",
    "Sjálfstæðisflokkinn": "Sjálfstæðisflokkurinn",
    "Viðreisn": "Viðreisn",
    "Framsóknarflokkinn": "Framsóknarflokkurinn",
    "Flokk fólksins": "Flokkur fólksins",
    "Pírata": "Píratar",
    "VG": "Vinstrihreyfingin – grænt framboð",
    "Sósíalistaflokkinn": "Sósíalistaflokkurinn",
}


def fetch_polls():
    """Fetch structured poll data from Maskína's Tableau dashboard."""
    client = httpx.Client(follow_redirects=True)

    # Step 1: startSession
    start_url = (
        f"{TABLEAU_BASE}/vizql/w/{WORKBOOK}/v/{SHEET}/startSession/viewing"
        f"?:display_static_image=y&:bootstrapWhenNotified=true&:embed=true"
        f"&:language=en-US&:embed=y&:showVizHome=n&:apiID=host0&:redirect=auth"
    )
    r1 = client.post(start_url, headers={"Accept": "application/json"}, content=b"")
    r1.raise_for_status()
    body = r1.json()

    session_id = r1.headers.get("x-session-id", body.get("sessionid"))
    sticky_key = body.get("stickySessionKey", "")
    global_header = r1.headers.get("global-session-header", "")
    cookies = "; ".join(f"{c.name}={c.value}" for c in client.cookies.jar)

    # Step 2: bootstrapSession
    boot_url = (
        f"{TABLEAU_BASE}/vizql/w/{WORKBOOK}/v/{SHEET}"
        f"/bootstrapSession/sessions/{session_id}"
    )
    form_data = {
        "worksheetPortSize": '{"w":1100,"h":1800}',
        "dashboardPortSize": '{"w":1100,"h":1800}',
        "clientDimension": '{"w":1003,"h":1022}',
        "sheet_id": ACTIVE_TAB,
        "stickySessionKey": sticky_key,
        "renderMapsClientSide": "true",
        "isBrowserRendering": "true",
        "browserRenderingThreshold": "100",
        "formatDataValueLocally": "false",
        "locale": "en_US",
        "language": "en",
    }
    r2 = client.post(
        boot_url,
        data=form_data,
        headers={
            "Cookie": cookies,
            "global-session-header": global_header,
            "x-tsi-active-tab": ACTIVE_TAB,
        },
    )
    r2.raise_for_status()

    # Parse response
    chunks = re.split(r"\d+;(?=\{)", r2.text)
    json_chunks = [c for c in chunks if c.startswith("{")]
    data = json.loads(json_chunks[1])

    seg = (
        data["secondaryInfo"]["presModelMap"]["dataDictionary"]["presModelHolder"]
        ["genDataDictionaryPresModel"]["dataSegments"]["0"]
    )
    reals, strings = [], []
    for col in seg["dataColumns"]:
        if col["dataType"] in ("real", "float"):
            reals = col["dataValues"]
        elif col["dataType"] in ("cstring", "string"):
            strings = col["dataValues"]

    # Find bar kosningar worksheet pane columns
    viz_map = (
        data["secondaryInfo"]["presModelMap"]["vizData"]["presModelHolder"]
        ["genPresModelMapPresModel"]["presModelMap"]
    )
    bar_ws = viz_map["bar kosningar"]["presModelHolder"]["genVizDataPresModel"]
    pane_cols = bar_ws["paneColumnsData"]["paneColumnsList"]

    party_indices, pct_indices = None, None
    for pane in pane_cols:
        for vpc in pane.get("vizPaneColumns", []):
            indices = vpc.get("valueIndices", [])
            if not indices:
                continue
            first = indices[0]
            if first < len(strings) and strings[first] in PARTY_NAMES:
                party_indices = indices
            elif first < len(reals) and 0 < reals[first] < 1:
                sample = [reals[i] for i in indices[:8]]
                if all(0 < v < 1 for v in sample):
                    pct_indices = indices

    # Period count varies (was 3, is 4 as of 2026-07-21) — detect it live
    # rather than hardcoding, by finding the block size where the party
    # name is constant within each block and changes between blocks.
    def _detect_stride(party_names_seq, candidates=(3, 4, 5, 6)):
        n = len(party_names_seq)
        for s in candidates:
            if n % s != 0:
                continue
            if all(
                len(set(party_names_seq[b * s: b * s + s])) == 1
                for b in range(n // s)
            ):
                return s
        raise RuntimeError(f"could not determine period stride from {n} values")

    party_names_seq = [strings[i] for i in party_indices]
    stride = _detect_stride(party_names_seq)

    # Extract one row per party, all `stride` periods (index 0 = latest,
    # index -1 = last election "Kosningar '24").
    results = []
    for i in range(0, len(party_indices), stride):
        party_acc = strings[party_indices[i]]
        pcts = [round(reals[pct_indices[i + k]] * 100, 1) for k in range(stride)]
        results.append({
            "party": PARTY_NAMES.get(party_acc, party_acc),
            "pcts": pcts,  # [latest, ...intermediate periods..., election]
            "latest_pct": pcts[0],
            "change_vs_prev_period": round(pcts[0] - pcts[1], 1),
            "change_vs_election": round(pcts[0] - pcts[-1], 1),
        })

    return sorted(results, key=lambda r: -r["latest_pct"])


if __name__ == "__main__":
    for row in fetch_polls():
        print(
            f"{row['party']:<35} {row['latest_pct']:>5.1f}%  "
            f"(mán: {row['change_vs_prev_period']:+.1f}, kosn: {row['change_vs_election']:+.1f})"
        )

Sample Output

Verified live 2026-07-21 (periods: 1 June 2026 / 1 May 2026 / 1 April 2026 / 30 Nov 2024 election), sums to 99.9%:

Samfylkingin                         25.2%  (mán: -0.1, kosn: +4.4)
Sjálfstæðisflokkurinn                22.7%  (mán: +2.9, kosn: +3.3)
Miðflokkurinn                        14.2%  (mán: -0.8, kosn: +2.1)
Viðreisn                             12.4%  (mán: -2.0, kosn: -3.4)
Framsóknarflokkurinn                  8.5%  (mán: +0.7, kosn: +0.7)
Vinstrihreyfingin – grænt framboð     5.4%  (mán: +0.1, kosn: +3.1)
Flokkur fólksins                      4.1%  (mán: -0.6, kosn: -9.7)
Sósíalistaflokkurinn                  3.9%  (mán: +0.2, kosn: -0.1)
Píratar                               3.5%  (mán: -0.6, kosn: +0.5)

Flokkur fólksins' -9.7pt collapse since the 2024 election (13.8% → 4.1%) matches the well-documented real-world drop in their support — a useful sanity anchor when verifying future extractions.

Re-verified 2026-08-01 with the code block above run verbatim against the following month's poll (published 2026-07-22, "Sjálfstæðisflokkurinn á flugi"): Sjálfstæðisflokkurinn leads at 25.0%, all nine parties extract once each, sum exactly 100.0% — stride detection handled the new measurement without changes.

Data Caveats

1. VizQL API is undocumented — Tableau could change the response format without notice. The WordPress API is a stable fallback for prose data.
2. Accusative party names — Tableau data uses accusative case (þolfall). Must map to nominative for display. If a new party appears, the mapping needs updating.
3. Percentages as fractions — Values come as 0–1, multiply by 100.
4. global-session-header is NOT the session ID — It is a Base64-encoded routing value. Using the session ID instead causes 410 Gone on bootstrapSession.
5. Cookie forwarding required — The set-cookie headers from startSession must be passed as Cookie header to bootstrapSession.
6. Response size — bootstrapSession returns ~650KB. The data is in chunk 1 (~61KB); chunk 0 is layout metadata.
7. Monthly updates — Polls are published monthly. The dashboard updates automatically.
8. Time-period count is not fixed at 3 — detect it live. Verified live 2026-07-21: the dashboard now carries 4 periods per party (latest, previous month, month before that, last election), not the 3 originally documented here. A naive fixed stride silently desyncs party names from percentages and produces duplicate party rows with garbage values instead of erroring — the sum-of-percentages sanity check below is what caught it, not an exception. Always detect the stride from the data (see _detect_stride()), and sanity-check the result sums to roughly 100% before trusting it.
9. Sanity-check before trusting the output. sum(latest_pct for all parties) should land in the 95-105% range. If it doesn't (or if any party name repeats), the stride detection or column-matching heuristic picked the wrong valueIndices array — don't report the numbers as-is.

Alternative Sources

• maskina.is articles — WordPress REST API, prose format, full article text
• RÚV/Vísir/Heimildin — media coverage of polls from all pollsters; the skodanakannanir skill extracts numbers from those articles
• Gallup (gallup.is) — Competing polling firm; no direct integration, but its polls reach the skodanakannanir pipeline via news coverage
• Prósent (prosent.is) — Former MMR, another polling firm; same — reachable via skodanakannanir news coverage