Python Dataframe to JMP Datatable without intermediate csvIt looks like the interface between a python dataframe and a jmp datatable goes through a csv file. Is that true?
For example:
Python Init(Path("C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\python37.dll"));
Python Submit( "\[import pandas as pd
df = pd.read_parquet('c:/temp/tst.parquet')
]\" );
dt = Python Get(df); // this method is saving the df as csv and then opens it in jmp. Is there a way to do that in memory
dt << New Data View;
Python Term();
In the above code I see JMP opening a progress bar for reading a csv during the Python Get(df) call. This is taking a very long time in large files.
We would like a way to import the data-frame to data-table w/o the time to save as csv and reading it
Data AccessScriptingStatistics and AnalyticsRe: Python Dataframe to JMP Datatable without intermediate csv - Status changed to: ArchivedWe are archiving this request. If this is still important please comment with additional details and we will reopen. Thank you!Re: Python Dataframe to JMP Datatable without intermediate csvThanks for implementing this Wish in Jmp 18 
Re: Python Dataframe to JMP Datatable without intermediate csv@Sarah-Sylvestre - delivered?
Re: Python Dataframe to JMP Datatable without intermediate csv - Status changed to: DeliveredRe: Python Dataframe to JMP Datatable without intermediate csv@Sarah-Sylvestre, it looks like the Python dataframe still goes via a csv to become a JMP table. Am I misunderstanding something?
Re: Python Dataframe to JMP Datatable without intermediate csvJMP 14-17 Python Send ( dt ) created a copy of the data table as a pandas dataframe.
JMP 18_+ creates a jmp.DataTable object which is a live reference to the data.
Python Get ( dt ) get's a JSL reference to the Python data table object.
Python Get ( df ) creates a data table from a pandas dataframe that is a COPY of the data.
JMP 18 - Python Get ( df ) does indeed use CSV to get a DataFrame as JMP DataTable, that was left for compatibility. You should be making a dt from the df in Python and using the dt with Python Get().
JMP 19 adds Portable Dataframe Protocol support so that it is easy to create a JMP DataTable from a Pandas dataframe in memory without having to walk the columns and build columns yourself. dt = jmp.from_dataframe( df )
In JMP 19 Python Get ( df ) should create a new data table which is a COPY directly from the dataframe in memory. If it cannot automatically convert in memory for whatever reason, it falls back to CSV instead of failing.
