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  • Don’t miss your chance to experience Discovery Summit Europe at our best available rate! Early bird registration through 31 Oct.
  • Image to Table JMP extension imports single or batch images as data tables. Useful to extract curves from pictures or convert image data to curve data to use in analyses like Functional Data Explorer. Download and install the extension.
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Latest Discussions

  • JMP18 Excel Save Behavior

    Hello Community! When saving a table of character columns as an xlsx Excel file, JMP18 adds some kind of invisible flag that makes Excel think it is has numbers stored as text. This is a different behavior than JMP17 and is causing data interpretation issues on downstream non-JMP scripts that use this Excel file. Any advice on how to work around this or change this behavior? I cannot change the co...

    obstruksion obstruksion
    Discussions |
    Sep 9, 2025 9:58 AM
    1341 views | 2 replies
  • Quickly show Data View with subset of rows that match regex

    I'm looking for a JSL script that does the following:   Gets the currently selected columns in the active data table. Takes the first selected column. Prompts the user to enter a regular expression. Selects only the rows in the table where the value in that column matches the regex. Opens a Data View window showing only those matching rows.   Is this possible with JSL?

    BHarris BHarris
    Discussions |
    Sep 9, 2025 8:10 AM
    4521 views | 10 replies
  • Evaluate performance linear fit VS log fit

    Hi all,   I was wondering if you have any suggestions on how to evaluate the performance of a linear model and log model (i.e. only response logarithmic transformed). I am trying to evaluate which model is better in terms of predictability and accuracy. My first guess was to compare R-squared values and RMSE values, however I seems that two models have different units and therefore cannot be direc...

    Janneman Janneman
    Discussions |
    Sep 9, 2025 7:20 AM
    3458 views | 5 replies
  • How to Exclude Random Missing point before performing PCA.

    Hi,   How to exclude missing values from the dataset before analysis. These are random missing values due to instrument malfunction. I don't want to impute my data. I have explored the 'Explore Missing Value' but that didn't help because that changes the interpretation of my PCA results.   Is there any other way to do so?   Thank you, Beginner_9

    Beginner_9 Beginner_9
    Discussions |
    Sep 9, 2025 6:48 AM
    3091 views | 6 replies

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