# 可视化专题

内容准备中，虽不充分，但做为基础资料分享或许对一些朋友也有所帮助。以后相关部分会专题化维护，内容持续更新，相关题材内容根据本身性质规则分享。

# 重点推荐

非常优秀的数据可视化网站，你可以通过决策树来选择你合适的图表，非常方便易用。不同的是这里有各种收录的图表的基本介绍，并添加的『常见错误』来帮助你正确的可视化数据。并且提供了 R、python 和 D3 的示例代码[见下图]；

同时提供了一些常见可视化错误案例，还制作了决策树的海报，你可以通过购买海报来支持项目[见下图]。

了解图表应用，和图表作者的分析思路（深入分析数据特性，有效可视化）

后续会更新到 DC checklist 的 mini checlist

Visualization highlights the key takeaway

The data visualization is designed with your specific audience in mind
Chart type is appropriate for the data – e.g. use a line chart for
demonstrating trends over time
Objects work together to clearly highlight a finding or takeaway message
Limit the use of complex ‘fancy’ charts to avoid confusing or misleading your audience – keep it simple

Strategic arrangement of elements can make a data visualization easier to interpret

The number of charts in the view is limited to four
Proper use of real estate; the more important elements in the view should
take up more space
Chart axes should start at 0 (unless there’s a specific need to alter)
The spaces between X & Y axis intervals should be even and they should be clearly labeled.
Data is displayed in a logical order (e.g. chronological, magnitude, etc.)
Ensure proper sizing of elements in the visualization (avoid scroll-bars, or
scrunched up charts)

Titles, labels, annotations, and other text forms help communicate your message

Removing unnecessary elements in the view can significantly improve its quality and impact

Gridlines are not present or muted (light gray)
Redundant borders are removed
Axes tick marks are used with appropriate spacing
Values are formatted to a suitable level of precision (round up) and apply applicable display units (e.g. thousands, currency)
Currency symbols are used, when applicable
Graphs are 2 dimensional; avoid 3D or shape bevels
Any icons or images are used to support interpretation
Data legends (color, size, or shape) are positioned near the relevant data and used sparingly

Proper use of color will help tell your data story; while a poor one will confuse or distract your audience

Color is used to highlight key patterns and guides the viewer
Supporting data is muted (light gray)
Patterns are still viewable when printed in black and white
Color scheme is intentional (e.g. in line with brand)
Color is legible for people with colorblindness
Culture-laden color connotations have been considered
Not more than 5 colors are used in the visualization
Consistent color is used for same variables
Gradient diverging color palette is not used for categorical data nor for background
Sufficient contrast exists to ensure readability

等我看完的

——《论语》