



**NumPy** is a free Python library equipped with a collection of complex mathematical operations suitable for processing statistical data. It can be imported into Python as follows: 



import numpy as np 
# The np label can be used to access the numpy library

# Numerical data in machine learning

**Data manipulation** is a core component in data sciences and machine learning. In the case of machine learning, the system takes in a huge amount of data and trains itself to make accurate predictions. Naturally, it would need to perform arithmetic operations on numerical data to produce something meaningful. This is where NumPy comes into play.
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# Basic functions of NumPy

The main data structure in NumPy is the NumPy array. All the data is stored in arrays. NumPy provides a vast repertoire of mathematical and statistical operations which can be performed on these arrays.

import numpy as np

arr_1 = np.array([1, 2, 3, 4, 5, 6])
fltr = [True, False, True, False, True, False]

# filtering elements of an array
arr_2 = arr_1[fltr]
print(arr_2)

Filtering

import numpy as np

arr_1 = np.array([1, 2, 3, 4, 5, 6])
arr_2 = arr_1.reshape(3, 2)

# reshaping an array
print(arr_2)

ReshapingArrays

import numpy as np

arr_1 = np.array([1, 2, 3, 4, 5, 6])

# sum of an array
print(arr_1.sum())

Aggregation

import numpy as np

arr_1 = np.array([1, 2, 3])
arr_2 = np.array([4, 5, 6])

# adding two numpy arrays
print(np.add(arr_1, arr_2))

ArrayArithmetic

import numpy as np

arr_1 = np.array([1, 2, 3, 4, 5, 6])

# standard deviation
print(np.std(arr_1))

StatisticalModels

What is NumPy?

NumPy is a free Python library equipped with a collection of complex mathematical operations suitable for processing statistical data. It can be imported into Python as follows: 

What is NumPy?

Numerical data in machine learning

Basic functions of NumPy

Code