In this video, we show how to use local data filtering in JMP. Data filtering makes it easy to update a graph or an analysis based on values of other variables in the data set.
We use the Scrapped Parts scenario for illustration. This is data about scrapped parts collected for 811 batches over a three-month period. For each batch that had at least one scrapped part, data were collected about the number of pieces scrapped, the total value of the scrapped parts, the product line, and the product family.
To show local data filtering, we’ll first create a graph. For this video, we’ll create a bar chart for Product Line using Graph Builder from the Graph menu.
We drag Product Line to the X zone, drag Pieces to the Freq zone, and click Done to close the control panel. This produces a bar char for the number of pieces scrapped for each defect category.
We see that product lines A2 and A3 have the most scrapped parts.
We also have information about Product Family. Do product lines A2 and A3 have the most scrapped parts across all of the product families?
To explore this, we use a data filter. To access the local data filter, we select the option from the red triangle.
From the list of variables in the Local Data Filter panel, we select Product Family and click the plus sign.
When we click on a category in the Local Data Filter, the graph updates to show only values from this category.
For example, we see that most scrapped parts for the Extra Large product family are from product line B1, and the biggest category for Large parts is product line B2.
Note that the local data filter filters only the current platform. If you want to apply a data filter to the data table and all future analyses, you can use a global data filter.
To use the global data filter, we first remove the local data filter. Then we select Data Filter from the Rows menu.
This is similar to the local data filter, but it enables you to interact with the data table.
We again select Product Family. When we select a category, the data filter selects the corresponding values in the data table and in all open graphs.
When we click Show, the data filter hides all of the other observations in the data table. These observations are also hidden in graphs.
When we click Include, the data filter excludes the other observations in the data table. These observations will be excluded from future analyses that you run.
There are many red triangle options in both the local data filter and the global rows data filter. For more information about these options, search for Data Filter or Local Data Filter in the JMP Help at www.jmp.com/help.