Highest temperature in Sao PauloPolymarket historical data and price history

Highest temperature in Sao Paulo: a Polymarket weather series with markets recurring daily. Marketlens has captured 1,243 markets since July 7, 2026, of which 1,263 resolved, with $4.7M in traded volume. No new markets were collected from July 24, 2026 to August 2, 2026, so windows inside that gap return nothing. Before that, 42 markets from February 28, 2026 to March 9, 2026 predate continuous coverage and are the only data before it. Order books are stored at full depth, with every individual price change captured at millisecond resolution on the most actively traded markets, alongside trades, candles, and the final resolution outcome.

For the weather archive as a whole, see Polymarket weather market data.

Data as of 2026-11-02 · Polymarket series Sao Paulo Daily Weather · slug sao-paulo-daily-weather

Markets
1,285
Resolved
1,263
Traded volume
$4.7M
Avg volume / market
$3.8K
Cadence
daily
Coverage from
2026-07-07
Data through
now
Category
Weather

No new markets were collected from July 24, 2026 to August 2, 2026, so windows inside that gap return nothing. Before that, 42 markets from February 28, 2026 to March 9, 2026 predate continuous coverage and are the only data before it.

Resolution outcomes

No: 1,144 (90.6%)Yes: 119 (9.4%)

Outcomes across 1,263 resolved markets with a recorded winning outcome. Settlement in the archive is by winning outcome, not by final traded price.

Markets in this series

The most recently resolved of 1,285 markets.

Will the highest temperature in Sao Paulo be 25°C on November 1?

closed 2026-11-02 · volume $2.4K · resolved No

Will the highest temperature in Sao Paulo be 22°C on November 1?

closed 2026-11-02 · volume $253 · resolved No

Will the highest temperature in Sao Paulo be 28°C on November 1?

closed 2026-11-02 · volume $615 · resolved No

Backtest this series

python
from datetime import datetime, timedelta, timezone from marketlens import MarketLens, Strategy class MyStrategy(Strategy): def on_market_start(self, ctx, market, book): ctx.buy_yes(size=10) client = MarketLens() end = datetime.now(timezone.utc) - timedelta(days=1) result = client.backtest( MyStrategy(), "sao-paulo-daily-weather", after=end - timedelta(hours=1), before=end, initial_cash=1_000, ) result.show() # inspect the run in the dashboard

Available datasets

Order book snapshots and deltasfull L2 depth, millisecond price changes
Tradesindividual fills with side and size
CandlesOHLC at multiple resolutions
Bulk Parquet exportsfull markets for offline research
Backtestingtick level replay with realistic fills

Common questions

How many Highest temperature in Sao Paulo markets are in the archive?

1,243 markets from July 7, 2026 through now, of which 1,263 have resolved and 22 are active. No new markets were collected from July 24, 2026 to August 2, 2026, so windows inside that gap return nothing. Before that, 42 markets from February 28, 2026 to March 9, 2026 predate continuous coverage and are the only data before it.

What data exists for each Highest temperature in Sao Paulo market?

Full depth L2 order book snapshots at regular intervals, individual trades, OHLC candles, and the resolution outcome, with the full price change stream at millisecond resolution on the most actively traded markets in the series. All of it is queryable by the series slug "sao-paulo-daily-weather" through the API and Python SDK, or downloadable as Parquet.

How often do Highest temperature in Sao Paulo markets resolve No?

Of 1,263 resolved markets with a recorded outcome, 1,144 resolved No (90.6%) and 119 resolved Yes.

How much does a typical Highest temperature in Sao Paulo market trade?

Average traded volume is $3.8K per market, $4.7M across the series.

Can I backtest strategies on Highest temperature in Sao Paulo?

Yes. Pass the slug "sao-paulo-daily-weather" to client.backtest() in the Python SDK. Execution mode replays order books against real historical depth; Alpha mode, one bar per market, covers every market in the series and suits its longer horizons.

Related series: Highest temperature in Hong Kong, Highest temperature in London, Highest temperature in Seoul (Incheon), Highest temperature in Shanghai, Highest temperature in NYC, Highest temperature in Paris, or all weather series.

Try it

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bash
$ pip install marketlens