I am working with a csv file that I have imported to JMP for analysis (I like the graphs and statistical analyses that I can perform with JMP). However, the file is rather large, and I execute a lot of code in R. At the end of my R script, I export the data to a csv, upload it to JMP, and perform my analyses.
This works great until I need to go back into R to change an equation. I end up doing the following:
1) Run the revised script in R
2) Export the data table from R as a csv file
3) Open the csv file in JMP
4) Update the old datatable in JMP with the new data from the csv file
Steps 1 & 2 aren't too bad, but step 3 really takes a long time. Is there a way I can just refresh my old JMP datatable without having to open the new CSV in JMP and then update the old data table with the new data table in JMP?
Thanks in advance!
Ah, that was something I had looked at, but was hoping to avoid, since the script I had put together starts with a big dataframe, runs calculations, then spits out several "little" dataframes. Rather than send a little dataframe back to R for some recalculation, I was hoping to just run the modified R script on the big dataframe, have it spit out a new little dataframe, which I could then access on JMP.
But using the interface you referred to is definitely something I could do, I was just hoping there was an alternative that didn't involve redoing my R script (I may be "intermediate" with JMP, but I'm a toddler with R, and writing scripts takes me a while to get right).
Part of what I'm doing in R involves some calculations, and part is just data reorganization. The biggest reason I'm using R is to force myself how to learn this, as it seems a lot of our organization uses this. The things I really like about JMP is that it's fairly quick for generating graphs & pivot tables on the go (which is great, as a lot of my meetings require me to generate novel graphs on-the-fly). But R is nice for working on really large datasets (I've moved into situations where I'm having to start with millions of rows of data), so for right now I'm using R for my calculations but then JMP for my final analysis.
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