Python and BIG Data analytics | Python Fundamentals | Python Architecture

© 2015 Blue Camphor Technologies (P) Ltd. www.skillspeed.com Slide 1
Python for Big Data
Analytics

Session Objectives
This session will help you to understand:
ᗍ Introduction to Python
ᗍ Web Scraping Use Case
ᗍ Introduction to Big data
ᗍ Getting your doubt’s cleared

What is Python?
ᗍ Python is a general purpose High-level Programming Language designed to be easy to read and simple
to implement
ᗍ It’s high-level built in Data Structures, combined with dynamic typing and dynamic binding, makes it very
attractive for Rapid Application Development
ᗍ Python supports Modules and Packages, which encourages Program Modularity (feature of subdividing a
program into separate sub-programs) and Code Reuse
ᗍ It is similar to PERL and RUBY but with certain differences such as Object-oriented features

What is Python? (Cont’d)
Python has Object-oriented Structure. It supports:
Polymorphism
Static
Polymorphism
Runtime
Polymorphism
Class A
Class B Class C
Polymorphism Multiple Inheritance Object Overloading
Operator ‘+’
5+5=10
Skill+Speed
=SkillSpeed
Get Started with Python

Why Python?
Good for Text Processing
Generates HTML Content
Your C++ Program
Extended in C and C++
Script.py
Cpython
Interpreter
Cpython
Interpreter
Clear Syntax

Why Python? (Cont’d)
Interpreted Environment
Source Code
Interpreter
Output
Automatic Memory Management
Good for Code Steering and for
Merging Multiple Programs
Supports Library Utilities and Third Party
Utilities (Example: Numeric, NumPy, SciPy)

Job Trends
PercentageGrowth

Users of Python
Google App Engine is an eminent sample of Python-written application, it
allows building web applications with Python programming language, using its
rich collection of libraries, tools and frameworks
YouTube is a big user of Python, the entire site uses Python for different
purposes: view video, control templates for website, administer video, access
to canonical data, and many more. Python is everywhere at YouTube
Amazon Web Services uses Python

Some More Users of Python

System Utilities GUIs (Tkinter) Internet Scripting Embedded Scripting
Database Programming Artificial Intelligence Image Processing
Major Uses of Python

Demo: Web Scraping – Flipkart.com
ᗍ This Example demonstrates how to extract data from flipkart for a particular product like “Watch”
ᗍ We shall use requests (Python Package) which gets the web page for you, then you need to parse the HTML from
the page to retrieve the data. That is done by BeautifulSoup

ᗍ Big data is the term for a collection of data sets so large and complex that it becomes difficult to process
using on-hand database management tools or traditional data processing applications
ᗍ Huge Amount of Data (Terabytes or Petabytes)
ᗍ The challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualization
ᗍ Many systems or a collection of systems generates these huge data, few examples are Space Exploration,
Deep Sea Navigation, Social Media etc.
What is Big Data?

Why Big Data?
ᗍ Data being generated today is so huge that traditional systems are unable to process it neither are able to
store it
ᗍ To create better DSS (Decision Support System) system
ᗍ Google alone receives 4 million search queries per minute
ᗍ Data is generated from everywhere such as Sensors for Climate Information, Social Media, Music Audio’s and
Videos, Global Positioning System
ᗍ Only 10 percent of worlds data today resides in RDBMS and 90% elsewhere, how do we deal with this
enormous data?

Big Data Statistics
Every minute:
ᗍ Facebook users share nearly 2.5 million pieces of content
ᗍ Twitter users tweet nearly 300,000 times
ᗍ Instagram users post nearly 220,000 new photos
ᗍ YouTube users upload 72 hours of new video content
ᗍ Apple users download nearly 50,000 apps
ᗍ Email users send over 200 million messages
ᗍ Amazon generates over $80,000 in online sales
Refer: http://aci.info/2014/07/12/the-data-explosion-in-2014-minute-by-minute-infographic/

Characteristics of Big Data

Case Study 1: Big Data from Space
Satellite Imaging

ᗍ Structure of Data:
Data in social media are unstructured or semi-structured. Data from twitter /Facebook are in JSON. where do we
store it? How do we process it?
ᗍ Quantity of Data:
These are tons of unstructured, structured and semi structured data. How do I derive a pattern out of it?
ᗍ Processing of Data:
How do we process this complex data structure, what technologies do we use?
ᗍ Prediction Algorithm:
After having done all the good work of cleansing and slicing/dicing the data, which algorithm do we use. Is it
decision tree, SVM, k-mean, kNN and the list goes on
Case Study 2: Social Media Analytics

Why SkillSpeed?
Course
Curriculum
from Industry
Experts
Instructor Led
Live Virtual
Sessions
Lifetime access
to Course
Content via
LMS
100% Placement
Assistance
24x7 Support

Course Topics
Module 1
Introduction to Python
Module 2
Built-In Data Types, Strings,
Sequence and Files
Module 3
Functions, Sorting, Exceptions,
Standard Libraries
Module 4
Regular Expression and
Object-oriented Programming
Module 5
Debugging Python, Project
Skeleton in Python and SQLite
Database
Module 6
Introduction to Big Data and
Hadoop
Module 7
Python and Big Data
Module 8
Implementation of Machine
Learning in Python
Module 9
Working Examples of
Machine Learning in Python
Module 10
Project Implementation

Corporate Partners

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References
https://harshbhimjyani.wordpress.com/2014/10/21/scraping-flipkart/
https://www.vlab.org/sandbox/events/satellite-imaging-big-data-from-space-shared/
http://www.datasciencecentral.com/profiles/blogs/data-veracity

Python and BIG Data analytics | Python Fundamentals | Python Architecture

Python and BIG Data analytics | Python Fundamentals | Python Architecture

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