Snowpark for Python - Hands-on-Lab - Weather Data by Pelmorex Weather Source
收藏Snowflake2022-05-05 更新2024-11-12 收录
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https://app.snowflake.com/marketplace/listing/GZSOZ1LLE9
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资源简介:
Snowflake users can use this tile to instantly and securely access up-to-date weather information to uncover ML-powered insights on the ridership and inventory demand for Citibike - a bike sharing system in New York. To access the hands-on-lab visit https://quickstarts.snowflake.com/
Pelmorex Weather Source is a leading provider of global weather and climate data and our OnPoint Product Suite provides businesses with the necessary weather and climate data to quickly generate meaningful and actionable insights for a wide range of use cases across industries.
Pelmorex Weather Source powers a majority of Fortune companies who use our data to quantify the impact of weather and climate on various KPIs including footfall traffic, product sales and demand, supply chain and logistics, advertising and more.
Sample Dataset:<br/>OnPoint Historical Weather Data in daily format for New York City ZIP Code - 10007. The sample data is in Celcius and covers the time period from June 1, 2013 to present. The data is updated daily and includes includes the following supported weather parameters: precipitation, temperature, wind speed & direction and humidity.
About the Provider:<br/>Pelmorex Weather Source helps businesses turn weather uncertainty into a predictive advantage. With 35+ years of weather experience, 250+ global clients, 50+ meteorologists, and 100+ tech and data experts, we deliver trusted data and insights that integrate seamlessly to drive measurable ROI.
Weather Source’s Complete Onpoint Data Products Include:
- High-resolution data for every landmass on Earth and up to 200 miles offshore.
- Daily/hourly historical data from 2000 to present.
- Daily/hourly 15-day forecast data with an enhanced view out to 46 days.
- Daily/hourly climatology data.
提供机构:
Pelmorex Weather Source
创建时间:
2022-05-05
搜集汇总
数据集介绍

背景与挑战
背景概述
该数据集提供纽约市特定区域的每日历史天气数据(摄氏温度),包含降水、温湿度等关键气象参数,时间跨度为2013年至今,每日更新。数据源自专业气象服务商Pelmorex,适用于商业分析和机器学习应用。
以上内容由遇见数据集搜集并总结生成



