sas-jmp

问题 I'm trying to figure out how to use JSL to write some of the analysis of variance variables values to a table in JMP. My idea is to write a script that runs different types of models with different parameters with R^2 and RSME logging to a table (maybe there is a better way to do this I'm on my second day of JMP). Going through the documentation it seems that different analysis have different ways of doing this and I can't find one for "fit model". I also will need to know how to do this for

问题 I am struggling to read SAS JMP files with Pandas read_csv function into Pandas dataframe. Does anyone have experience with this type of data file? What is the most efficient way? 回答1: This has worked for me. Its results are sometimes a bit unexpected (for example, sometimes I get CSVs without headers, even though in JMP they have them). Unfortunately, you need to have SAS JMP installed and this solution only works on Windows. import pandas as pd from win32com.client import Dispatch jmp =

问题 Most built-in Python data types and libraries make a point of returning the same object ( a is b , not just a==b ) even if you ask for it in different ways. A very simple example: list = [ "foo", "bar", {"name": [1,2,3]} ] a = list[-1]["name"] b = list[2].values()[0] print (a is b) # True! However, this doesn't seem to be the case for many kinds of non-scalar objects returned by win32com automation. The following code connects to sas-jmp automation and then gets two handles to the same data

问题 I'm trying to automate a process that JMP does (Analyze->Distribution, entering column A as the "Y value", using subsequent columns as the "weight" value). In JMP you have to do this one column at a time - I'd like to use Python to loop through all of the columns and create an array showing, say, the median of each column. For example, if the mass array is [0, 10, 20, 30], and the weight array for column 1 is [30, 191, 9, 0], the weighted median of the mass array should be 10. However, I'm