如何消除Spotfire箱形图中的异常值 [英] how to eliminate outlier in spotfire box plots

问题描述

谢谢您的帮助.

关于， 拉吉

推荐答案

将值添加到MAX()值将扭曲数据，即使可能的话.不过，有两个技巧可以做到这一点.

Adding the values to MAX() values would skew the data even if it were possible. There are two hacks to do this though.

1. 右键单击>属性> Y轴>将MIN范围值和MAX范围值设置为可以消除所有异常值的值.这实际上仅适用于所有值都彼此接近(所有百分位数)的箱形图.
2. 在工具栏上，单击插入">计算列">选择正确的数据表并粘贴在下面的表达式中.您将需要用箱形图的X和Y轴上的内容替换[x-axisColumn]和[y-axisColumn].要找出这是什么，请右键单击您的箱形图>属性> X轴，然后它将告诉您X轴列是什么.还要对Y轴执行此操作.这将在数​​据表中创建一个名为"Outlier"的列，其中包含三个选项:NotOutlier，UpperOutlier，LowerOutlier.您只需要取消选中"UpperOutlier"和"LowerOutlier"即可删除离群值.

1. Right Click > Properties > Y-Axis > set the MIN range value and MAX range values to something that would eliminate all outliers. This is really only suitable for box plots that are close in all values to each other (all percentiles)
2. On your toolbar click Insert > Calculated Column > choose the correct data table and paste in the expression below. You will need to replace the [x-axisColumn] and the [y-axisColumn] with what ever is on the X and Y axis of your box plot. To find out what this is, right click on your box plot > properties > X-Axis and there it will tell you what your X-Axis column is. Do this for the Y-Axis as well. This will create a column called "Outlier" in your data table with three options: NotOutlier, UpperOutlier, LowerOutlier. You just need to uncheck "UpperOutlier" and "LowerOutlier" to remove your outliers.

`

case
when [y-axisColumn]<(Q1([y-axisColumn]) - (1.5 * IQR([y-axisColumn]) OVER ([x-axisColumn]))) then "LowerOutlier"
when [y-axisColumn]>(Q3([y-axisColumn]) + (1.5 * IQR([y-axisColumn]) OVER ([x-axisColumn]))) then "UpperOutlier"
else "NotOutlier"
end as [Outlier]

`

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