July 2017
Intermediate to advanced
398 pages
11h 54m
Chinese
Content preview from Python数据处理
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196
｜
第
9
章
UNICEF
的数据，或者聚焦于一个国家，利用
UNICEF
的多指标类集调查数据来理解过去
几十年发生的变化。
对于你自己的数据集，你需要确定未来探索时有哪些可能性。你能找到更多的数据以供探
索吗？你是否可以访问一些人，或者在一段较长的时间中找到一些趋势？是否有这一主题
的书籍、电影或者文章能够给你更多启发？你的分析是未来研究的开始。
9.2.2
你的数据在讲什么
现在我们已经探索和分析了数据，可以开始搞清楚数据在告诉我们什么。正如我们在第一
次研究童工数据集时经历的那样，有时数据并没有什么联系，没讲述任何故事，没有任何
相关性。发现这一点也没关系！
有时候，没找到相关性将促使我们继续研究，以找到真正存在的联系。有时
候，没找到联系，这件事情本身就是一个发现。
在数据分析中，我们寻找趋势和模式。正如我们在童工雇用数据中看到的那样，大多数时
候分析是更深入研究的开始。和数据讲故事一样，增加人们的声音或者其他的角度，都是
找到联系和发现问题的绝佳方式。
如果你发现了一些联系，即使是很弱的联系，也可以更深入地挖掘。这些联系会通向更
好的问题和更专注的研究。正如我们在童工数据中看到的那样，我们对研究越专注，就
越容易看到联系。从宽泛的研究开始是很好的，但是用更加精确的视角来结束研究十分
重要。
9.2.3
描述结论
当你已经分析了数据并且理解了数据中的联系，就可以开始确定你能得出什么结论。真正
了解你的数据集和主题非常重要，这会对你的想法提供强有力的支持。随着你的数据分
析、访谈、研究的完成，你的结论会逐渐形成，你只需要确定用什么方式来向全世界分享 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.