topic Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table in Discussions

Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

zetaVagabond1 — Fri, 17 Oct 2025 08:49:20 GMT

Context:
I am using JMP 18 with Python integration to merge multiple datasets. The merge and processing in Python works correctly using pandas, but when I try to send the final pandas DataFrame back to JMP using Python Get(), the resulting JMP Data Table is empty. I want to create a JMP table from my pandas DataFrame in Python and access it in JSL.

Example of What I’m Trying:

// Send JMP tables to Python
Python Send(jmp_table1);
Python Send(jmp_table2);

// Python processing
Python Submit("
import pandas as pd

def jmp_to_pandas(jmp_table):
    cols = list(jmp_table)
    data_dict = {}
    for col in cols:
        data_dict[col.name] = list(col)
    return pd.DataFrame(data_dict)

# Convert JMP tables to pandas DataFrames
df1 = convert_jmp_to_pandas(jmp_table1)
df2 = convert_jmp_to_pandas(jmp_table2)

# Merge tables
merged_df = pd.merge_asof(df2, df1, left_on='Time', right_on='Time', direction='nearest')
");

// Attempt to bring merged DataFrame back to JMP
dt_merged = Python Get(merged_df);
dt_merged << Set Name("Merged_Data");
dt_merged << Show Window;

Problem Observed:

dt_merged is created but contains no data. [but the data frame is generated as I can save it to csv and use it]
Using global in Python does not seem to fix the issue.
Python Get() does not appear to recognize the pandas DataFrame correctly.

What I Want:

Convert a pandas DataFrame into a JMP table from Python.
Access it in JSL with proper name, show the window, and manipulate columns.
Avoid creating empty tables and maintain all rows/columns.

Potential Solutions I’m Considering:

Exporting to CSV from Python and then importing to JMP - tried and works but it's something I don't want.
Ensuring the DataFrame is declared global before Python Get(). - didn't work

Environment:

JMP 18
Python 3.x (embedded)
Using inside a JSL script

Any guidance or working examples of sending pandas DataFrames back to JMP from Python would be greatly appreciated!

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

jthi — Fri, 17 Oct 2025 09:07:05 GMT

Check out the "Building a Pandas DataFrame by Looping Through Data Table Columns" example from Scripting Guide > Python > Creating a Pandas DataFrame from a JMP Data Table . Also I think in JMP19 this is easier Python Dataframe to JMP Datatable without intermediate csv (JMP Wish List) but I haven't tried yet due too multiple issues with JMP19.

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

Paul_Nelson — Fri, 17 Oct 2025 13:51:35 GMT

Your dt_merged does contain data, it does not contain a view.

use

dt_merged << New Data View;

instead of

dt_merged << Show Window;

The table exists but doesn't yet have an associated window.

Also note that in JMP 18 Python Get( df ) does use dataframe -> CSV CSV -> data_table internally just like JMP 14-17 did. Only the JMP data table has live access to the data across JMP / Python boundaries.

In JMP 19 the situation is much better. JMP supports the Portable Dataframe Protocol and it's a 1 line of code to go from a JMP dt => a pandas DataFrame and another 1 line to go DataFrame to DataTable. This works for any dataframe like package that supports the DataFrame Protocol and the conversion occurs in memory.

Your other choice is creating the merged data table in Python using the jmp.DataTable APIs and walking the dataframe columns creating JMP columns one by one in the new data table. Looks like you have time data as part of the tables. This takes care to get correct. In JMP 14-18 you have to marshal between JMP's data time representation and Python's data time representation. Epoch date for JMP is Jan 1, 1904 ( same as Excel on the Mac) vs Python's Epoch Date is Jan 1, 1970.

JMP 19 properly marshals datetime values across the JSL / Python boundaries.

There are examples in the 'Python' section of the scripting index, for the jmp import package.

I would highly recommend updating to JMP 19. JMP 18 was a foundational change to Python Integration in JMP . While JMP 18's support was not as complete as we would have liked, it provided so much capability we did not want to hold off until JMP 19.

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

Paul_Nelson — Fri, 17 Oct 2025 14:03:45 GMT

I also want to point out that that the jmp.DataTable object is iteratable so you can directly use jmp_table in your for loop. It already behaves like a list of columns

def jmp_to_pandas(jmp_table): data_dict = {} for col in jmp_table: data_dict[col.name] = list(col) return pd.DataFrame(data_dict)

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

zetaVagabond1 — Tue, 28 Oct 2025 06:47:17 GMT

I did observe the dates in my dataframe are quite bizzare please refer the screenshot. this is date format and only few are affected, date-time doesn't seem to be affected.

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

hogi — Tue, 28 Oct 2025 07:15:52 GMT

This is date in seconds. you can display any number as date by changing the column settings:

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

zetaVagabond1 — Tue, 28 Oct 2025 09:32:47 GMT

Hey thanks, I figured this out but I am working with jsl and python code in between. Is there a better way to take care of this in the code itself.

1 - process in python using epoch time offset

2- reassign the column format to each columns in the jsl code. [tedious]

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

hogi — Wed, 29 Oct 2025 07:44:37 GMT

:col << Format( "yyyy-mm-dd" );

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

zetaVagabond1 — Tue, 28 Oct 2025 11:11:18 GMT

The screenshot was an example, I have 100s of columns :\ , with inconsistent formatting in the source data . Thanks btw

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

hogi — Tue, 28 Oct 2025 11:37:08 GMT

JMP19?

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

zetaVagabond1 — Wed, 29 Oct 2025 02:44:41 GMT

JMP 18, org not migrating to JMP19 , I am not sure whether its a test version roll-out or a developed application. I suspect later one.

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

hogi — Wed, 29 Oct 2025 05:44:32 GMT

Maybe wait for JMP19.1 to get some missing features back:

besides that:

one of the reasons to switch to JMP19: from_dataframe()

another reason: wonderful improvements in the data grid like Column Tags and Filter Views.

Do you have the chance to install JMP19 "manually" on a test system ?

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

zetaVagabond1 — Wed, 29 Oct 2025 08:17:53 GMT

Yes , I can do that. I have not done it. Another reason I am not using that is the script compatibility as other users would continue using JMP18. I am already facing quite alot of issues with table referencing and joins.

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

hogi — Wed, 29 Oct 2025 08:19:52 GMT

@zetaVagabond1 wrote:

I am already facing quite alot of issues with table referencing and joins.

Issues with JMP18 vs. JMP17?

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

Paul_Nelson — Wed, 29 Oct 2025 18:30:28 GMT

JMP uses a Jan 1, 1904 epoch for time 0 in seconds ( Mac Excel epoch date)

Python uses the standard UNIX Jan 1, 1970 epoch date for time 0 in seconds.

JMP 19 properly marshals date time values across JSL / Python boundaries.

JMP 19 has a dt = jmp.from_dataframe(df) that will create a date table directly from the data frame in memory.

In JMP 18 the only in-memory choice is to build the columns yourself, looping on the pandas columns and paying attention to date/time conversion.

Alternatively, you could go through CSV. That's the way it was done in JMP 14-17. But be aware you can get small binary differences in numerics when going binary -> CSV -> binary. There are samples in JMP 18's SAMPLE_SCRIPTS/Python directory that show how to go the CSV route. Basically, tell pandas to save as csv, then tell JMP to open the CSV.

I really suggest you upgrade to 19. Dramatic improvements to data table handling have been made in 19.

Re: Issue Sending Pandas DataFrame from Python to JMP 18 Data Table

hogi — Wed, 29 Oct 2025 22:06:02 GMT

Rory Vaden: How to multiply your time?
https://www.youtube.com/watch?v=y2X7c9TUQJ8

Here: Wait today for your IT department to switch to JMP19 - maybe invest some effort to convince them.
Then you can write and use some great code tomorrow.

The alternative is to start today writing code that is already outdated today.

Python with JMP19:
- easy to code
- slim
- much faster