numpyprint 0.1.4

prints numpy arrays nicely

NumpyPrint

Numpyprint uses the Package prettytable to print numpy arrays in a nice format. At the moment this works well until a 2D Dimension.

Installation

pip install numpyprint

or

python3 -m pip install numpyprint

What is it ?

NumpyPrint nicely prints an numpy array with the help of the package PrettyTable. It prints arrays of any dimension.

Example

import numpy as np
from numpyprint import np_print

numpy_array = np.random.rand(1,2,3)*100
np_print(numpy_array)

The output with the default settings looks like this:

+---+----------------------------+---------------------------+
| 0 | +---+--------------------+ | +---+-------------------+ |
|   | | 0 | 40.361415789985486 | | | 0 | 89.54304456427288 | |
|   | | 1 | 42.44964170184573  | | | 1 | 43.11298502039822 | |
|   | | 2 | 19.234562477482196 | | | 2 |  40.0682288789328 | |
|   | +---+--------------------+ | +---+-------------------+ |
+---+----------------------------+---------------------------+

It prints a nice table with frame boarders and row numbers.

How to use it

Print to Console

import numpy as np
import numpyprint as npp

array = np.random.rand(3, 2, 3)*100

npp.np_print(array)

# or with change of some settings

npp.np_print(array,precision= 2 ,row_numbers= True, column_numbers= True,odd_vertical= False,style='plain')

Use in Jupyter Notebook

In Jupyter Notebook is it possible to use HTML to format the output. The following command prints the numpy array in a nice table.

import numpy as np
import numpyprint as npp

array = np.random.rand(3, 2)

npp.np_display(array)

Get the PrettyTable Object

If you want the PrettyTable object you can use np_format()

import numpy as np
import numpyprint as npp

array = np.random.rand(3, 2)

table = npp.np_format(array)

Change the Default Settings

The defaults are:

defaults=dict({
    'row_numbers': True,
    'column_numbers': False,
    'precision': None, # None or int like 2
    'style': 'default', # 'default' or 'plain'
    'odd_vertical': True
})

It is possible to change it like:

import numpy as np
import numpyprint as npp

npp.defaults['precision'] = 2