# Daily Temperature Paris Last Month for Retail Demand

**Use case:** 

Scrape daily temperature data for Paris for the past month, essential for understanding consumer behavior related to weather. Retail businesses can use this ins

## Input

```json
{
  "mode": "historicalWeather",
  "latitude": 48.8566,
  "longitude": 2.3522,
  "locationName": "Paris, France",
  "startDate": "2024-03-01",
  "endDate": "2024-03-31",
  "temperatureUnit": "celsius",
  "precipitationUnit": "mm",
  "windSpeedUnit": "kmh",
  "maxItems": 50
}
```

## Output

```json
{
  "date": {
    "label": "Date"
  },
  "latitude": {
    "label": "Latitude"
  },
  "longitude": {
    "label": "Longitude"
  },
  "tempMaxC": {
    "label": "Temp max c"
  },
  "tempMinC": {
    "label": "Temp min c"
  },
  "precipitationMm": {
    "label": "Precipitation mm"
  },
  "windSpeedKmh": {
    "label": "Wind speed kmh"
  },
  "sourceUrl": {
    "label": "Source url"
  }
}
```

## About this Actor

This example demonstrates how to use [NOAA Climate Scraper](https://apify.com/crawlerbros/noaa-climate-scraper) with a specific input configuration. Visit the [Actor detail page](https://apify.com/crawlerbros/noaa-climate-scraper) to learn more, explore other use cases, and run it yourself.


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This Task's input is already configured above — use it as-is rather than inventing a new one.

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For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/crawlerbros/noaa-climate-scraper.md

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).