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Archive for March 26th, 2020

The concept of “dimensional” in numpy is different with dimensional in math. In Math, dimensions is defined as the minimum number of coordinates needed to specify points within a space. So, 1 dimension consist of 1 variable X , 2 dimensions consist of 2 variables X &Y and 3 dimensions consist of 3 variables X,Y & Z.

Meanwhile dimensional in python is a container of items of the same type and size.The dimension can consist of of 1 or multi dimensional container. That’s why it named N-dimensional array.
I will give you examples.
Open your Linux Terminal, run python and type the code below.

Sample for 1 dimensional array

$ python3
Python 3.6.9 (default, Nov 7 2019, 10:44:02)
[nGCC 8.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> x=np.array([1,2,3])
>>> x
array([1, 2, 3])
>>> x.ndim
1
>>> x.shape
(3,)
>>>

This is 1 dimensional array that consist of 3 columns.

Sample for 2 dimensional array

>>> x=np.array([[1,1],[2,2]])
>>> x
array([[1, 1],
       [2, 2]])
Display the dimension
>>> x.ndim
2

Display the array shape

>>> x.shape
(2, 2)

You can read it as 2 ‘1-dimensional array’ ([1,1] and [2,2]) that each of it consist of 2 columns ([1,1] and [2,2]).

>>> x=np.array([[1,1,1],[2,2,2]])
>>> x
array([[1, 1, 1],
       [2, 2, 2]])
>>> x.ndim
2
>>> x.shape
(2, 3)

You can read it as 2 ‘1-dimensional array’ ([1,1,1] and [2,2,2]) that each of it consist of 3 columns ([1,1,1] and [2,2,2]).

>>> x=np.array([[1,1,1],[2,2,2],[3,3,3]])
>>> x
array([[1, 1, 1],
       [2, 2, 2],
       [3, 3, 3]])

It’s still 2 dimensional.

>>> x.ndim
2
>>> x.shape
(3, 3)
>>>


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In this article, I will explain in a simple way about Numpy (Numeric Python). Numpy is part of SciPy group, an open source python libraries that are designed for scientific computing that python can’t provide. There are others library that part of SciPy, which are Matplot Lib and Pandas.

By using Numpy, you can increase your python performance in computing numerical calculation significantly. Since, it’s very basic, I will not explain about specific data structure like N-dimensional array.

Numpy was developed by Travis Oliphant and released in 2006. The version Numpy is unified from Numarray which is developed by Jim Hugunin in 1995. Both of the package has their own power. And now, we have it both in one package.

Before we start, make sure you have install numpy in your Linux system.
To install numpy in python, type this command in your Linux Terminal.

$pip install numpy

I use Xubuntu 18.04 and python 3.6.9 when I write this article. So, by default the python version is still 2.7.15+ (default, Oct 7 2019, 17:39:04). Since, I use python 3.6.9 (default, Nov 7 2019, 10:44:02), the ‘pip’ install will be different.

The command is:

$pip3 install numpy

After all done, let’s try. Run your python and type the codes below:

import numpy as np
a=np.arange(0,10)
print(a)

This command, will create an array with consist of “0,1,2,3,4,5,6,7,8,9”.

$ python3
Python 3.6.9 (default, Nov 7 2019, 10:44:02)
[GCC 8.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> a=np.arange(0,10)
>>> print(a)
[0 1 2 3 4 5 6 7 8 9]
>>>


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