July 2017
Intermediate to advanced
398 pages
11h 54m
Chinese
Content preview from Python数据处理
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199
第 10章
展示数据
你已经学习了如何分析数据，现在想要展示它。针对不同听众，演示可能会有很大的差
别。我们会在这一章学习多种不同类型的演示：从简单的可以在电脑上制作的演示文件到
交互式的网站。
取决于你想要展示的内容，通过图表、地图或图片进行可视化可能是你尝试讲的故事中一
个重要的部分。我们会学习如何构建并运行自己的站点，分享发现。还会介绍如何分享
Jupyter notebook
，其他人通过它可以看到你的代码、图表、图片和结论。
首先，我们会探索如何考虑你的听众，开始讲述你通过数据分析发现的故事。
10.1
避免讲故事陷阱
讲故事并不简单。取决于主题，你可能很难从数据中得出可靠的结论。你可能会遇到不一
致或不确定的数据。这没关系。建议你继续研究，也许在数据集中找到的不同示例中就蕴
含着故事。
讲故事时所面临的一些困难是由数据分析时的个人偏见带来的。正如经济
学家和记者
Allison Schranger
在“
The Problem with Data Journalism
”（
http://
qz.com/189703/the-problem-with-data-journalism/
）一文中讨论的，我们不可
避免地会在分析时带有偏见。她的建议是，承认这些偏见，并试着去了解数
据，避免为了讲故事的目的而去曲解它。
不要擅自假定你所要讲的故事和数据是一致的。尝试先研究数据，然后讲述数据研究所
得。不要花太多时间来操作数据。如果需要大量修改数据（标准化、归一化和去除离群
值），你可能应该找找其他故事或不同的数据。
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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.