Python: Extract, Manipulate and Analyze Data with 5 Projects

Python: Extract, Manipulate and Analyze Data with 5 Projects
Python: Extract, Manipulate and Analyze Data with 5 Projects
English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 6.5 Hours | 1 GB

Learn how to extract, manipulate and analyze data using Python

Does your profession require you to deal with large data on a regular basis?

Do you wish you could be better at dealing with those numbers?

This course brings about a solution for you by teaching you how to manipulate and analyse the data in the most basic language, Python.

This course doesn’t only seek to teach you about data analysis but also helps you learn how to apply it in real-life situations. Apart from detailed programs on learning the basics of Python and the art of data analysis using Python, the course provides you with five projects that are real-life case studies.

Starting with the basics of Python, learn how to analyse big data, visualise them, and become an entry-level data analyst.

Here is an outline of what we’ll cover through the entire course:

  • Preparing your environment and software installation
  • Logical and looping constructs
  • Dealing with functions
  • Modules and packages
  • Dealing with file I/O in Python
  • Working on different data types such as CSV, JSON, RDBMS, and Excel
  • Dealing with non-relational database management systems
  • Dealing with web-related data
  • Data analysis and visualisation using DataNitro
Table of Contents

1 – Introduction to Course

2 – Preparing your environment
Choosing the right IDECode editor
Installing python on windowslinuxmac
Playing with pip and installing packages
Playing with the python shell
Writing your first python code and running it under different environments

3 – Beginning with Basics
Dealing with variables and string
Introduction with important built-in types in python – Part A
Introduction with important built-in types in python – Part B
Introduction with important built-in types in python – Part C
Numbers and different operators in python- Part A
Numbers and different operators in python- Part B

4 – Logical and looping constructs
Handling the errors and exceptions inn our decisions
Making decisions through if-else clauses
Repeating or looping the decisions multiple times and stopinng them
Understanding logical operators and expressions

5 – Dealing with functions
Calling functions from other function
Creating your first function
Nesting functions
Understanding input parameters and return type in functions
Writing recursive functions

6 – Modules & Packages
Organizing your code into modules and packages

7 – Dealing with file I_O in Python
Dealing with our first file and using write operation
Exploring the OS package to play with paths and directories
Handling file errors
Reading from files and processing the text

8 – What is Data Science
What is data Science and what does data scientists do
Why python for data analysis and other data related tasks

9 – Understanding RDBMS
Case Study
Dealing with postgresql using python
Installing postgresql on different platforms
Introduction to POSTGRESQL
Introdunction of RDBMS
Playing with postgresql

10 – What are the other data sources out there
Case Study
Dealing with CSV using Python
Dealing with EXCEL using python
Dealing with JSON using python
Dealing with XML using Python
Excel Processing – Part 1
Excel Processing – Part 2
Introdunction with different data sources
Understanding CSV
Understanding EXCEL
Understanding JSON
Understanding XML

11 – Dealing with Non-Relation database management systems
Brief introdunction to Big Data
Getting Down with MONGODB
Installing MONGODB on your Platfrom
Interacting with MONGODB with python using PYTMONGO
MONGODB – The first Introduction
What is NOSQL

12 – Dealing with Web Data
Case Study
Creating a simple web sraper using python
Dealing with scraped data using NOSQL
The Introduction to Requests and Beautiful Soup module – Part A
The Introduction to Requests and Beautiful Soup module – Part B
Understanding the WEB world Why would need data from web
Web Scraper Solution
What is Web Scraping

13 – Data Analysis and Visualization
Brief Introduction to NUMPY and PANDAS
Case Study
Data Visualization Example
Playing with your Data Frame
Visualizing and understanding your scraped data. Getting down with MATPLOTL
What is Data Analysis & What are its applications

14 – Data Nitro
Basics Operation of Data Nitro
Case study
Charts in Data Nitro
Data Nitro Example
Introduction to Data Nitro
What is EDA (Exploratory Data Analysis)

15 – Downloadable Practice Files
Downloadable Files