Filtering large car data set based on criteria such as price, age, and odometer

[#1]

Some of my car data does not make sense such as, a car from 2020 with 2506000 milage and a high price. How do I set up filter conditions based on my criteria. For example set conditions to exclude cars with:

• Unusually high prices.
• Unusually low or high ages.
• Unusually high odometer readings.

[#2]

you can open a "global" data filter:

hogi_0-1701536659210.png

select the strange entries and then use the inverse option to show/include just the remaining rows:

hogi_1-1701536831520.png

[#3]

If the strange cars show up in a combination of properties, like you say: 
car from 2020 with 2506000 milage

then you can plot the data, select the strange data points, and then label the selected rows
e.g. via Rows/Row Selection /Name Selection in Column.

Alternative - with more options:  the want tool from  QuickSelect Toolbar 

hogi_3-1701537330039.png

After labelling the outliers, you can either use the labels in Graph Builder to investigate further on the details - or use the label column to remove the labelled entries from the analysis:
"???" means: no label

hogi_5-1701537521968.png

[#4]

You can use the Exploring Outliers analysis if you want to have JMP identify outliers for you

     Analyze=>Screening=>Explore Outliers

JMP Help has a good deal of information on how to run the analysis.

You can also manually explore your data by setting up a Data Filter

      Rows=>Data Filter

If you choose this route, you can setup the Data Filter to filter on Prices, Ages and Odometer Reading.  Then you can open multiple platforms such as Distribution, Graph Builder etc. and the displays will automatically change as you modify your selection criteria in the Data Filter.

JMP Help also has details on how to setup and run the Data Filter