NumPy - Part1

NumPy (Numerical Python) is the fundamental package for scientific computing in Python. It provides a multidimensional arrayobject, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays,including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.

Why we need numpy when we have list?/Why numpy is so popular?

• Provide faster operation for Large Scale operation
• Behind the scene optimizations written in C
• Vectorization via broadcasting(avoiding loops)s
• Backbone of other python scientifi c packages

Numpy dataTypes and Attributes

Main datatype of Numpy is ndarray, where ndarray represent n dimentional array.

import numpy as np

import pandas as pd #Details of pandas library will be cover in Pandas chapter.

a1 = np.array([1,2,3])

print(a1)

print("Type of the array is {}".format(type(a1)))

print("\nData type of the array is {}".format(a1.dtype))

print("\nShape of the array is {}".format(a1.shape))

print("\nSize of the array is {}".format(a1.size))

print("\nDimention of the array is {}".format(a1.ndim))

print("\n",pd.DataFrame(a1))

O/P

[1 2 3]

Type of the array is <class 'numpy.ndarray'>

Data type of the array is int64

Shape of the array is (3,)

Size of the array is 3

Dimention of the array is 1

    0

0  1

1  2

2  3