JMP file question
Hi, Is there a way for me and a collegue to work on the same JMP file in real time? We have JMP 17. Thanks!
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view all learning resourcesHi, Is there a way for me and a collegue to work on the same JMP file in real time? We have JMP 17. Thanks!
I have created a representation of my data using graph builder that I am happy with. I would like to include Passing Bablok fits, as this is the most appropriate method in this case. I know I can do this via bivariate fitting separately (and I have done so), but the graphical representation as well as the advanced fitting together is what I am after. How can I achieve this?
I am getting a termination error every time I run jmp2pandas. The table is formed, but then the termination error appears (see attached image). import jmp2pandas import pandas as pd data = { "Name": ["Alice", "Bob", "Charlie"], "Age": [25, 30, 35], "City": ["New York", "London", "Paris"] } df = pd.DataFrame(data) jmp2pandas.df2dt(df,dt_title='Example df to dt')
Hi everyone-
I am losing my mind trying to figure this out. I believe the answer lies in some magical combination of Eval() and Expr() but I can't figure it out.
I have a list of columns I want to define at the beginning of the script and then reference for use as model effects, as shown below. How do I get the model to recognize the list as a list of columns to use as effects? Thank you!
JMP 19...
We are considering offering JMP to our employees running on an Azure Virtual Desktop (AVD). Is anyone else doing this? Has this been considered a viable option? Are there any system requirements or limitations we should be considering?
Hi, Is there a way for me and a collegue to work on the same JMP file in real time? We have JMP 17. Thanks!
I have created a representation of my data using graph builder that I am happy with. I would like to include Passing Bablok fits, as this is the most appropriate method in this case. I know I can do this via bivariate fitting separately (and I have done so), but the graphical representation as well as the advanced fitting together is what I am after. How can I achieve this?
I am getting a termination error every time I run jmp2pandas. The table is formed, but then the termination error appears (see attached image). import jmp2pandas import pandas as pd data = { "Name": ["Alice", "Bob", "Charlie"], "Age": [25, 30, 35], "City": ["New York", "London", "Paris"] } df = pd.DataFrame(data) jmp2pandas.df2dt(df,dt_title='Example df to dt')
Hi everyone-
I am losing my mind trying to figure this out. I believe the answer lies in some magical combination of Eval() and Expr() but I can't figure it out.
I have a list of columns I want to define at the beginning of the script and then reference for use as model effects, as shown below. How do I get the model to recognize the list as a list of columns to use as effects? Thank you!
JMP 19...
We are considering offering JMP to our employees running on an Azure Virtual Desktop (AVD). Is anyone else doing this? Has this been considered a viable option? Are there any system requirements or limitations we should be considering?
Previous versions of JMP would let users select multiple columns and use the "Replace missing with previous value" option from the right-click drop-down menu, applying the function to all columns selected. With JMP19, I can only do it if I select one column at a time. Is there a way to keep doing with with multiple columns selected?
Looking for the Best way to analysis Data when I have Ranges Upper, Mid and Lower for both Voltage and Freq. data. See RED Columns. Guess I could perform a Control Chart or Dist. but like to to see if their is a shift of this many Electrical Devices. Any Suggestions?
[Environment]
Version: JMP(r) Student Edition 19.1.0 (914688)
License: For Academic Use Only (Expires: 2027/04/13)
OS: Microsoft Windows 11 Home (10.0.26200.0)
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Why don't all three of these return their unevaluated argument like the first one does? Is there a way to make the last two work like the first? Inside the function, e is still unevaluated, this seems to happen when the result is returned.
names default to here(1);
ns = New Namespace("n");
foo = function({e}, Name Expr(e) );
ns:bar = function({e}, Name Expr(e) );
show( foo( expr( notavar...
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