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  <channel>
    <title>topic JMP 19 Python Integration: ValueError: year 0 when converting Data Table to Pandas in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/JMP-19-Python-Integration-ValueError-year-0-when-converting-Data/m-p/942295#M109501</link>
    <description>&lt;DIV class="Y3BBE" data-processed="true" data-complete="true" data-hveid="CAEIBxAA" data-sfc-cb="" data-sfc-root="c" data-sfc-cp=""&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;Hello Everyone,&amp;nbsp;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;I am upgrading my scripts from JMP18&amp;nbsp; to JMP19&amp;nbsp; and 'm hitting a particular roadblock with this integration. In JMP 18, I used custom function to loop through columns and create Pandas DataFrame. It worked perfectly. However in JMP19, the exact code throws a&amp;nbsp;&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;ValueError: year 0 is out of range.&amp;nbsp;&lt;/CODE&gt;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;Here is the snippet:&amp;nbsp;&lt;/CODE&gt;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;
&lt;PRE&gt;&lt;CODE class=" language-jsl"&gt;Python Send("raw_data");&lt;/CODE&gt;&lt;/PRE&gt;
&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;&lt;/CODE&gt;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;
&lt;PRE&gt;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)
&lt;/PRE&gt;
&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;data1 = jmp_to_pandas(raw_data)&lt;/CODE&gt;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;&lt;/CODE&gt;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;&lt;/CODE&gt;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;
&lt;DIV class="Y3BBE" data-processed="true" data-complete="true" data-hveid="CAEICxAA" data-sfc-cb="" data-sfc-root="c" data-sfc-cp=""&gt;&lt;STRONG&gt;Questions:&lt;/STRONG&gt;&lt;/DIV&gt;
&lt;OL class="IaGLZe VimKh" data-processed="true" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;
&lt;LI class="dF3vjf" data-sae="" data-complete="true" data-hveid="CAEIDBAA" data-sfc-cb="" data-sfc-root="c"&gt;&lt;SPAN class="T286Pc" data-complete="true" data-sfc-cb="" data-sfc-root="c" data-sfc-cp=""&gt;What is the official JMP 19 way to convert an open Data Table to a Pandas DataFrame?&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI class="dF3vjf" data-sae="" data-complete="true" data-hveid="CAEIDBAB" data-sfc-cb="" data-sfc-root="c"&gt;&lt;SPAN class="T286Pc" data-complete="true" data-sfc-cb="" data-sfc-root="c" data-sfc-cp=""&gt;Has the&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;jmp&lt;/CODE&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;module structure changed? I'm finding it difficult to locate the updated JMP 19 Python API reference on the website.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI class="dF3vjf" data-sae="" data-complete="true" data-hveid="CAEIDBAC" data-sfc-cb="" data-sfc-root="c"&gt;&lt;SPAN class="T286Pc" data-complete="true" data-sfc-cb="" data-sfc-root="c" data-sfc-cp=""&gt;How should "Year 0" or JMP null dates (1904 epoch) be handled in JMP 19 to avoid Python datetime crashes?&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/OL&gt;
&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;&lt;/CODE&gt;&lt;/DIV&gt;
&lt;/DIV&gt;</description>
    <pubDate>Thu, 16 Apr 2026 06:06:51 GMT</pubDate>
    <dc:creator>zetaVagabond1</dc:creator>
    <dc:date>2026-04-16T06:06:51Z</dc:date>
    <item>
      <title>JMP 19 Python Integration: ValueError: year 0 when converting Data Table to Pandas</title>
      <link>https://community.jmp.com/t5/Discussions/JMP-19-Python-Integration-ValueError-year-0-when-converting-Data/m-p/942295#M109501</link>
      <description>&lt;DIV class="Y3BBE" data-processed="true" data-complete="true" data-hveid="CAEIBxAA" data-sfc-cb="" data-sfc-root="c" data-sfc-cp=""&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;Hello Everyone,&amp;nbsp;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;I am upgrading my scripts from JMP18&amp;nbsp; to JMP19&amp;nbsp; and 'm hitting a particular roadblock with this integration. In JMP 18, I used custom function to loop through columns and create Pandas DataFrame. It worked perfectly. However in JMP19, the exact code throws a&amp;nbsp;&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;ValueError: year 0 is out of range.&amp;nbsp;&lt;/CODE&gt;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;Here is the snippet:&amp;nbsp;&lt;/CODE&gt;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;
&lt;PRE&gt;&lt;CODE class=" language-jsl"&gt;Python Send("raw_data");&lt;/CODE&gt;&lt;/PRE&gt;
&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;&lt;/CODE&gt;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;
&lt;PRE&gt;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)
&lt;/PRE&gt;
&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;data1 = jmp_to_pandas(raw_data)&lt;/CODE&gt;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;&lt;/CODE&gt;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;&lt;/CODE&gt;&lt;/DIV&gt;
&lt;DIV class="Y3BBE" data-sfc-cp="" data-sfc-root="c" data-sfc-cb="" data-hveid="CAEIBRAA" data-complete="true" data-processed="true"&gt;
&lt;DIV class="Y3BBE" data-processed="true" data-complete="true" data-hveid="CAEICxAA" data-sfc-cb="" data-sfc-root="c" data-sfc-cp=""&gt;&lt;STRONG&gt;Questions:&lt;/STRONG&gt;&lt;/DIV&gt;
&lt;OL class="IaGLZe VimKh" data-processed="true" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;
&lt;LI class="dF3vjf" data-sae="" data-complete="true" data-hveid="CAEIDBAA" data-sfc-cb="" data-sfc-root="c"&gt;&lt;SPAN class="T286Pc" data-complete="true" data-sfc-cb="" data-sfc-root="c" data-sfc-cp=""&gt;What is the official JMP 19 way to convert an open Data Table to a Pandas DataFrame?&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI class="dF3vjf" data-sae="" data-complete="true" data-hveid="CAEIDBAB" data-sfc-cb="" data-sfc-root="c"&gt;&lt;SPAN class="T286Pc" data-complete="true" data-sfc-cb="" data-sfc-root="c" data-sfc-cp=""&gt;Has the&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;jmp&lt;/CODE&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;module structure changed? I'm finding it difficult to locate the updated JMP 19 Python API reference on the website.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI class="dF3vjf" data-sae="" data-complete="true" data-hveid="CAEIDBAC" data-sfc-cb="" data-sfc-root="c"&gt;&lt;SPAN class="T286Pc" data-complete="true" data-sfc-cb="" data-sfc-root="c" data-sfc-cp=""&gt;How should "Year 0" or JMP null dates (1904 epoch) be handled in JMP 19 to avoid Python datetime crashes?&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/OL&gt;
&lt;CODE class="KDcb0c" dir="ltr" data-sae="" data-complete="true" data-sfc-cb="" data-sfc-root="c"&gt;&lt;/CODE&gt;&lt;/DIV&gt;
&lt;/DIV&gt;</description>
      <pubDate>Thu, 16 Apr 2026 06:06:51 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/JMP-19-Python-Integration-ValueError-year-0-when-converting-Data/m-p/942295#M109501</guid>
      <dc:creator>zetaVagabond1</dc:creator>
      <dc:date>2026-04-16T06:06:51Z</dc:date>
    </item>
    <item>
      <title>Re: JMP 19 Python Integration: ValueError: year 0 when converting Data Table to Pandas</title>
      <link>https://community.jmp.com/t5/Discussions/JMP-19-Python-Integration-ValueError-year-0-when-converting-Data/m-p/942305#M109502</link>
      <description>&lt;P&gt;&lt;LI-MESSAGE title="Going further with Python in JMP 19" uid="898522" url="https://community.jmp.com/t5/JMPer-Cable/Going-further-with-Python-in-JMP-19/m-p/898522#U898522" discussion_style_icon_css="lia-mention-container-editor-message lia-img-icon-blog-thread lia-fa-icon lia-fa-blog lia-fa-thread lia-fa"&gt;&lt;/LI-MESSAGE&gt;&amp;nbsp;is most likely a good starting point&lt;/P&gt;</description>
      <pubDate>Thu, 16 Apr 2026 06:34:10 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/JMP-19-Python-Integration-ValueError-year-0-when-converting-Data/m-p/942305#M109502</guid>
      <dc:creator>jthi</dc:creator>
      <dc:date>2026-04-16T06:34:10Z</dc:date>
    </item>
    <item>
      <title>Re: JMP 19 Python Integration: ValueError: year 0 when converting Data Table to Pandas</title>
      <link>https://community.jmp.com/t5/Discussions/JMP-19-Python-Integration-ValueError-year-0-when-converting-Data/m-p/943465#M109572</link>
      <description>&lt;P&gt;For the latest information on the&amp;nbsp;&lt;STRONG&gt;import jmp&lt;/STRONG&gt; object's API see the Scripting Index 'Python' category in JMP. &amp;nbsp;Documentation and sample code provide the latest updates. &amp;nbsp;There are significant updates to the jmp module in 19. &amp;nbsp;&lt;/P&gt;
&lt;P&gt;Given your function, I would say it's Pandas that is throwing the ValueError:. &amp;nbsp;Pandas has changed between its Python 3.11 version used in 18 and the Python 3.13 version utilized in JMP 19. &amp;nbsp;&lt;/P&gt;
&lt;P&gt;See the Scripting index example on jmp.DataTable.from_dataframe(). &amp;nbsp;There are multiple examples there, both to and from JMP data tables and other dataframe compatible Python objects: &amp;nbsp;Pandas; Polars; Ibis; ...&lt;/P&gt;
&lt;P&gt;Specifically, 'Pandas to JMP' and 'JMP to Pandas' examples.&lt;/P&gt;
&lt;P&gt;JMP to Pandas sample:&lt;/P&gt;
&lt;LI-CODE lang="python"&gt;import jmp
import jmputils

try:
    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

dt = jmp.open(jmp.SAMPLE_DATA + "Big Class.jmp")
pandas_df = (pd.api.interchange.from_dataframe(dt))
print(pandas_df) &lt;/LI-CODE&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 22 Apr 2026 13:39:03 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/JMP-19-Python-Integration-ValueError-year-0-when-converting-Data/m-p/943465#M109572</guid>
      <dc:creator>Paul_Nelson</dc:creator>
      <dc:date>2026-04-22T13:39:03Z</dc:date>
    </item>
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