time-series data

基本解釋

Graphite is a Python web application that has been developed to provide scalable storage and visualization for numeric time-series data.
Graphite是一個(gè) PythonWeb應(yīng)用，用來(lái)為數(shù)字時(shí)序數(shù)據(jù)提供可伸縮的存儲(chǔ)和可視化顯示。
In addition to the standard XML and JSON APIs, profile categories in AMEE can be viewed as Atom feeds, which are ideal for time-series data of the type we have been creating.
除標(biāo)準(zhǔn) XML 和 JSON API 以外，AMEE 中的配置文件類(lèi)別都可被視為 Atom 提要，這對(duì)于我們所創(chuàng)建的時(shí)間序列數(shù)據(jù)而言非常理想。
Finally, the results show the methods can effectively come into being regression analysis model of time-series data streams, and fulfill the prediction of future data streams.
最后，試驗(yàn)分析展示了研究結(jié)果能夠有效地產(chǎn)生時(shí)間序列數(shù)據(jù)流的回歸模型和實(shí)現(xiàn)數(shù)據(jù)流未來(lái)數(shù)據(jù)的預(yù)測(cè)。

In 2008, economists Justin Wolfers and Betsey Stevenson, both of the University of Pennsylvania, published a paper where they reassessed the Easterlin paradox using new time-series data.
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Mr. FELCH: Well, the big takeaway from our series - and after, you know, spending a lot of time analyzing this data - is that individual teachers really matter.
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