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精读《how we position and what we compare》 #50

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huxiaoyun opened this issue Dec 15, 2017 · 3 comments
Closed

精读《how we position and what we compare》 #50

huxiaoyun opened this issue Dec 15, 2017 · 3 comments

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@huxiaoyun
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huxiaoyun commented Dec 15, 2017

本篇文章以一个简单的例子,抽丝剥茧细数讲述如何面向用户可视化设计,化繁为简,化多为少,探索用户最终的目的,如何一张图中体现N张图的含义。具体内容,请和我一起走进 story telling data 系列 - how we position and what we compare http://www.storytellingwithdata.com/blog/2017/12/14/how-we-position-and-what-we-compare <---- 此处应该有 x 档案 bgm ....

提前剧透:

image

如何从左图变化到右图,难道作者是个拥有魔法棒的小仙女,还是可以点石成金的老神仙??一起详细看文章,魔法是如何修炼成功的。

image

哎哟,这里没有内容咯~~~ 评论区等你哦~

@huxiaoyun huxiaoyun changed the title 精读 how we position and what we compare 精读 《how we position and what we compare》 Dec 15, 2017
@huxiaoyun huxiaoyun changed the title 精读 《how we position and what we compare》 精读《how we position and what we compare》 Dec 15, 2017
@jasonslyvia
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想到之前看过一篇类似讲图表会骗人的文章,通过调整坐标轴的基数让原本差异不大的几组数据显得差异特别大 https://blog.heapanalytics.com/how-to-lie-with-data-visualization/

@huxiaoyun
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@jasonslyvia 是的呀。 人眼通过斜率和高度来对比差异,如果一不留神很容易被骗了。这让我想到,数据和语言一样,换种方式表达,翻译出来的意思就完全不同了,如果数据的表达方式能和语言一样,有一些固定的语法和规则,是不是能够减少表现上的歧义呢?

@ascoders
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人脑处理图形效率高于文字嘛,前端要做的也是提升人机交互效率,通过图形可以几倍甚至几百倍提高理解速度。

深度学习+可视化方向,就是不但让人类读懂图,让机器也读懂。未来可能很少会接触到数据化的数据,图形化数据可能成为标配,基于此的抽象会更有用,比如文中的图表转换。。

@ascoders ascoders mentioned this issue Dec 24, 2017
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