how to find the empty columns and delete them by scripting
how to find the empty columns and delete them by scripting. any helps and/or hints will be very appreciated.
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view all learning resourceshow to find the empty columns and delete them by scripting. any helps and/or hints will be very appreciated.
If I add an If-function to a column, the else-clause does not recognize empty values (see attached sheet). this means that the function:If( :Column 2 == 1, 1,2 )leaves missing values if Column 2 contains missing values. I can fix this by changing the function to:If( :Column 2 == 1, 1, Is Missing( :Column 2 ), 2)orIf( :Column 2 == 1, 1, Is Missing( :Column 2 ), 2, 2)but why is this necessary?...
By default, when you wrap graphs using the Graph Builder, it seems to order the graphs by the value of the column you use for wrapping, and label them with the same column. I would instead like to either wrap the graphs by column A and order them by column B, or alternatively, wrap them by column B and label them by column A.Ex:Date, Name, [Data]1/2/16, X-ray, [...]2/5/16, Alpha, [...]5/1/16, Brav...
As part of a database export I get a file with some headers that I can use straight away ( from Experiment ID to DOE_FILE_ID) but then I get some 'generic' headers of C1 to C255 what I need to do is to select all of the first row of data which has C1 to C255 as their headers and replace it with the information from the selected first row so C1 would be changed to Sample, C2 would be OLD Sampl...
Hi, i´m a new JMP user and I´m trying to perform different sets of general linear model in order to assess the best predictors of different dependent variables. I have read some publications reporting this kind of analyses and the partial eta squared coefficient is also reported as an index of effect size. If I use the standard least squares model in JMP, I get statistics for each independent fact...
Hi, i´m a new JMP user and I´m trying to perform different sets of general linear model in order to assess the best predictors of different dependent variables. I have read some publications reporting this kind of analyses and the partial eta squared coefficient is also reported as an index of effect size. If I use the standard least squares model in JMP, I get statistics for each independent fact...
how do i interpret PCA summary plots?
I see save session script but it seems to save everything starting from the beginning. Is there a way to save only part of the session having a set of consecutive clicks which can be rerun for similar other files?
Hello all,I am not able to find problem why it is not showing title name according to the variable "a1". Please find my script below.dt1 = open("F:\pushpendra\jmp\HIPO_RintCalculation.jmp");dt2 = open("F:\pushpendra\jmp\wafer.jmp");for(i=1,i<=nrow(dt2),i++, a1= Eval(column(dt2, 1)); biv=dt1<<Bivariate( Y( :Site_Value ), X( :Name( "Length(um)" ) ), Fit Line( {Line Color( "Red" )} ), where( :W...
I have read 350 .jpeg images into a JMP data table with the actual images in an Expression column. Can I then use Image Processing (e.g John Ponte script) on the images contained in the expression column?
Hi!I was wondering if anyone already tried to work with Co-Kriging, using JMP together with Matlab. As JMP only fits Ordinary Kriging Models (Gaussian Process with Gaussian Correlation Function), I would like to send data (generated with Space Filling JMP Platform) from JMP to Matlab, fit the models there (Matlab), and bring the MODELS back to JMP, to use inside Profile Platform. Do you have any e...
I'm trying to interpret the relative contributions of my variables in a discriminant function analysis of chemical data for three groups of rocks. In a stepwise, linear, common covariance discriminant function analysis I'm able to generate non-overlapping 95% confidence ellipses for my three groups with no incorrectly assigned data points using 6 variables. My understanding is that the scoring c...
A former classmate of mine from Graduate School has recently published a paper on Generalized Segmented Distributions. Utilizing this method, the distribution can approach any continuous density function of arbitrary form. The method is particularly effective in fitting data with sufficient observations that are skewed and/or multimodal. The paper can be found here:The General Segmented Distrib...
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