Additional Python Integration Examples

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Scripting Guide • Extending JMP • Working with Python • Additional Python Integration Examples

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Additional Python Integration Examples

Send a Data Table to Python

This example initiates a Python connection, sends a data table to Python, prints it to the log, and closes the Python connection.

dt = Open( "$SAMPLE_DATA/Big Class.jmp", invisible );

Python Send( dt ); // send the opened data table represented by dt to Python

Python Submit( "print( dt )" );

name age sex height weight

0 KATIE 12 F 59 95

1 LOUISE 12 F 61 123

2 JANE 12 F 55 74

Create Objects in Python

This example initiates a Python connection, creates a Python object, retrieves the object into JMP, and closes the Python connection.

Python Submit("\[

import numpy as np

import pandas as pd

# Generate basic series

ss = pd.Series(np.random.randn(5), index=['a', 'b', 'c', 'd', 'e'])

sn = pd.Series(np.random.randn(5))

# Generate Data Frames from Series

s1 = pd.Series(np.random.randn(5), index=['a', 'b', 'c', 'd', 'e'])

dfs1 = pd.DataFrame(s1)

d1 = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),

'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd'])}

dfd1 = pd.DataFrame(d1)

d2 = {'one' : [1., 2., 3., 4.],

'two' : [4., 3., 2., 1.]}

dfd2 = pd.DataFrame(d2)

ss = Python Get( ss );

Show( ss );

sn = Python Get( sn );

Show( sn );

dfs1 = Python Get( dfs1 );

dfs1 << New Data View;

dfd1 = Python Get( dfd1 );

dfd1 << New Data View;

dfd2 = Python Get( dfd2 );

dfd2 << New Data View;

Use Python Functions and Graphics

This example initiates a Python connection and plots the normal density function in Python using the Python graphics device, Then the graph is retrieved from Python and displayed in JMP. Finally, the Python connection is closed.

Python Submit("\[

import matplotlib.pyplot as plt

plt.plot([1, 2, 3, 4])

plt.ylabel('some numbers')

plt.show(block=False)

picture = Python Get Graphics( "png" );

New Window( "Picture", picture );

Wait( 10 );

Simple Matrix Multiplication in Python

This example initiates the Python connection, sends a matrix to Python, creates a matrix in Python, multiplies them together, returns the new matrix to JMP, and closes the Python connection.

v = [9 8 7, 6 5 4, 3 2 1];

m = [1 2 3, 4 5 6, 7 8 9];

ml = Python Execute( {v, m}, {a}, "\[

import numpy as np

a = np.multiply(v, m) # matrix product

]\" );

Show( a );