如何规范雷达图的统计 [英] how to normalize statistics for a radar chart

问题描述

我使用raphaelJS绘制一个雷达图来显示统计数据。对于每个轴，它应该接受介于0和10之间的值。

例如，多边形的中心点在图表中心的右边[10,10 ，10,10,10]。简单...

但是，可能会发生以下数据：

  [26,14,48,18,1]，
 [3,14,8,9,5]，
 [10，6，4，16，3] 
 

（显示多边形，其中心点在图表的左下方）：

如果我基于数据的最大值（在这种情况下为48）对数据进行归一化，所有其他中心点将太靠近图表的中心，并且其信息值将在0左右。 / p>

---

根据其最大值进行规范化的相同数据：

  [5.42,2.92,10,3.75,0.21]，
 [0.63,2.92,1.67,1.88,1.04]，
 [2.08,1.25,0.83,3.34,0.63 ] 
  

现在所有其他中心点都聚集在图表中心，并失去了所有的解释力。如果有超过3个中心点，它们很可能彼此重叠。

我正在考虑显示每个多边形的相对方式，而不是在每个多边形之间丢失太多的关系，如果可能的话...

将数据转换为

解决方案< //en.wikipedia.org/wiki/Logarithmic_scalerel =nofollow> logaritmic scale 不是一个选项？

这样一个极端值不会扭曲/拥挤其他价值观。只需计算数组值的常用/自然对数（例如，请参见 w3school页面上），然后将它们提供给图表API。

I'm using raphaelJS to draw a "radar chart" to display statistical data. For each axis it should accept values between 0 and 10.

For example, the vales of a polygon with its center point right in the center of the chart [10,10,10,10,10]. Simple...

However, it might happen that data looks like this:

[26, 14, 48, 18, 1],
[ 3, 14,  8,  9, 5],
[10,  6,  4, 16, 3]

which leads to this (displaying the polygon with its center point in the bottom left off the chart):

If I would normalize data based on its biggest value (in this case 48), all of the other center points would be too near to the center the chart, and and its informative value would be around 0.

---

same data normalized based on its biggest value:

[5.42, 2.92, 10,   3.75, 0.21],
[0.63, 2.92, 1.67, 1.88, 1.04],
[2.08, 1.25, 0.83, 3.34, 0.63]

So now all of the other center points are clustered in the center of the chart, and have lost all of their explanatory power... If there was more than 3 center points, they would most likely overlap each other.

I was thinking about a relative way to display each polygon, without losing too much relation between each polygon, if it's possible...

Any ideas how to do this, or maybe another approach how to normalize?

解决方案

Transforming your data to logaritmic scale is not an option?

That way a few extreme value would not distort/crowd the other values. Just compute the common/natural logarithm of the values of your array (e.g. see w3school page on it), and feed those to the chart API.

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