topic Re: issues running jmp2pandas.py in Discussions

issues running jmp2pandas.py

mhw_novonesis — Mon, 18 May 2026 20:25:45 GMT

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')

Re: issues running jmp2pandas.py

hogi — Tue, 19 May 2026 02:54:50 GMT

AI in the loop?

Re: issues running jmp2pandas.py

jthi — Tue, 19 May 2026 04:23:12 GMT

Which JMP version are you using?

Re: issues running jmp2pandas.py

mhw_novonesis — Tue, 19 May 2026 12:53:04 GMT

JMP 19.0.0

Re: issues running jmp2pandas.py

mhw_novonesis — Tue, 19 May 2026 13:15:06 GMT

Are you asking if AI is being used? or if AI is causing the error?

Re: issues running jmp2pandas.py

jthi — Tue, 19 May 2026 13:44:23 GMT

I would suggest using more modern methods to go from dataframe to datatable as you have JMP19 (jmp.from_dataframe)

import jmp

import jmputils

try:
    # pandas depends on numpy will install numpy if needed
    if not jmputils.is_installed('pandas'):
        jmputils.jpip('install', 'pandas', echo=False)
except Exception as e:
    print(f'Install failed with exception: {e}')

import pandas as pd
import numpy as np

pandas_df = pd.DataFrame(
    {
        "A": 1.0,
        "B": pd.Timestamp("20130102"),
        "C": pd.Series(1, index=list(range(4)), dtype="float32"),
        "D": np.array([3] * 4, dtype="int32"),
        "E": pd.Categorical(["test", "train", "test", "train"]),
        "F": "foo",
    }
)
print(pandas_df)

dt = jmp.from_dataframe(pandas_df)
print(dt)

See Scripting Index

Re: issues running jmp2pandas.py

christian-z — Thu, 21 May 2026 07:56:17 GMT

Agreed!

I guess @mhw_novonesis was using this reference: Creating a Pandas DataFrame from a JMP Data Table, but now there is the new function (as of JMP 19): jmp.from_dataframe()