Data Wrangling with Python

(DATA-WRGLG-PYTHON.AJ1)/ISBN:9781644593028

This course includes
Lessons
TestPrep
LiveLab
Mentoring (Add-on)

Use Data Wrangling with Python course and lab to gain an understanding of the concepts and methodologies associated with it. The data wrangling course and lab provide an understanding of the processes used along with the knowledge of the most popular tools and techniques in the domain. The Python course and lab also demonstrate how to use the Python back-end and extract/transform data from an array of sources including the Internet.

Lessons

10+ Lessons | 11+ Exercises | 72+ Quizzes | 84+ Flashcards | 84+ Glossary of terms

TestPrep

47+ Pre Assessment Questions | 53+ Post Assessment Questions |

Hand on lab

45+ LiveLab | 6+ Video tutorials | 07+ Minutes

Video Lessons

33+ Videos | 03:13+ Hours

Here's what you will learn

Download Course Outline

Lessons 1: Introduction

  • About the Course
  • Learning Objectives
  • Approach
  • Audience
  • Minimum Hardware Requirements
  • Software Requirements
  • Conventions
  • Installation and Setup

Lessons 2: Introduction to Data Wrangling with Python

  • Introduction
  • Python for Data Wrangling
  • Lists, Sets, Strings, Tuples, and Dictionaries
  • Summary

Lessons 3: Advanced Data Structures and File Handling

  • Introduction
  • Advanced Data Structures
  • Basic File Operations in Python
  • Summary

Lessons 4: Introduction to NumPy, Pandas, and Matplotlib

  • Introduction
  • NumPy Arrays
  • Pandas DataFrames
  • Statistics and Visualization with NumPy and Pandas
  • Summary

Lessons 5: A Deep Dive into Data Wrangling with Python

  • Introduction
  • Subsetting, Filtering, and Grouping
  • Detecting Outliers and Handling Missing Values
  • Concatenating, Merging, and Joining
  • Useful Methods of Pandas
  • Summary

Lessons 6: Getting Comfortable with Different Kinds of Data Sources

  • Introduction
  • Reading Data from Different Text-Based (and Non-Text-Based) Sources
  • Introduction to Beautiful Soup 4 and Web Page Parsing
  • Summary

Lessons 7: Learning the Hidden Secrets of Data Wrangling

  • Introduction
  • Advanced List Comprehension and the zip Function
  • Data Formatting
  • Identify and Clean Outliers
  • Summary

Lessons 8: Advanced Web Scraping and Data Gathering

  • Introduction
  • The Basics of Web Scraping and the Beautiful Soup Library
  • Reading Data from XML
  • Reading Data from an API
  • Fundamentals of Regular Expressions (RegEx)
  • Summary

Lessons 9: RDBMS and SQL

  • Introduction
  • Refresher of RDBMS and SQL
  • Using an RDBMS (MySQL/PostgreSQL/SQLite)
  • Reading Data from a Database in SQLite
  • Summary

Lessons 10: Application of Data Wrangling in Real Life

  • Introduction
  • Applying Your Knowledge to a Real-life Data Wrangling Task
  • An Extension to Data Wrangling
  • Summary

Hands-on LAB Activities

Introduction to Data Wrangling with Python

  • Sorting a List
  • Generating a List
  • Deleting a Value from a Dictionary
  • Accessing and Setting Values in a Dictionary
  • Slicing a String

Advanced Data Structures and File Handling

  • Implementing a Queue
  • Splitting a String
  • Implementing Multi-Element Membership Checking
  • Implementing a Stack
  • Opening a File and Printing its Content

Introduction to NumPy, Pandas, and Matplotlib

  • Generating Arrays Using arange and linspace
  • Multiplying Two Arrays
  • Adding Two NumPy Arrays
  • Creating a NumPy Array
  • Filtering Elements from a Matrix
  • Stacking Arrays

A Deep Dive into Data Wrangling with Python

  • Subsetting a DataFrame
  • Grouping a DataFrame
  • Dropping the Missing Values
  • Replacing Missing Values in a DataFrame
  • Joining DataFrames
  • Concatenating Data Frames
  • Counting Values

Getting Comfortable with Different Kinds of Data Sources

  • Bypassing the Headers of a CSV File
  • Reading Data from a CSV File
  • Stacking URLs from a Document Using bs4
  • Counting Tags

Learning the Hidden Secrets of Data Wrangling

  • Using the zip Function
  • Using a One-Liner Generator Expression
  • Using a Generator Expression
  • Using the format Function
  • Using a Box Plot

Advanced Web Scraping and Data Gathering

  • Checking the Status of the Web Request
  • Extracting Text from a Section
  • Traversing an XML Tree
  • Checking Whether the Input String Begins with a Specific Word
  • Matching Pattern
  • Finding the Number of Words in a List That End with ing

RDBMS and SQL

  • Deleting the Data
  • Using Joins
  • Using the Foreign Key
  • Updating Data
  • Using the ORDER BY Clause
  • Using the SELECT Statement
  • Using the SELECT Statement

Application of Data Wrangling in Real Life

  • Skipping the First Row of the Data Set