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prints numpy arrays nicely

Project description

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 it in Jupyter Notebooks

In Jupyter Notebook it is 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(). But keep in mind that multidimensional arrays have nested tables.

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/settings 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

Project details


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