Eliminate Negative values in multiple columns

[#1]

I have a table with 200 columns, and each column has negative values randomly populated. In some columns-like temperature- negative value is meaningful while performing summary statistics, but in others it is a filler for either "data not recorded- communication error" or "data not available- Equipment shut off". When I want to plot,  the negative values are useful. So my Q is how do I keep the negative values for plotting, while I am disregarding them while doing summary statistics? What are the different ways to approach this?

[#2]

Take a look at the Explore Outliers utility. It can help identify these values across all of your columns and convert them to a Missing Value Code.

Here's some more about Explore Outliers: . 

[#3]

Jeff,

 Thanks. I am not able to find Col--> Modeling Utilities in JMP16 as described in "Handling outliers at scale".

[#4]

The modeling utilities have moved to the Analyze->Screening menu.

 

 

[#5]

Thanks. I did see this, But was not sure if I am missing out on anything. Thanks again.

[#6]

One way that might work well, would be to make a copy of the data.  Delete all of the negative values in the copied data table.  Then add a new column to each data table, called "Negitives Included".  In the original table, set all of the rows for the new column to "Yes" and in the copied table, set all of the rows to "No".  Then use the Concatenate platform to put the 2 tables together.  Then you can run your plots and your statistics from the one table, using a Data Filter or a Local Data Filter to specify which data to use.