(DATA-WRGLG-PYTHON.AJ1) / ISBN : 978-1-64459-302-8
This course includes
Lessons
TestPrep
Hands-On Labs
AI Tutor (Add-on)
212 Review
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Lessons

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

TestPrep

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

Hands-On Labs

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

Video Lessons

33+ Videos | 03:13+ Hours

1

Introduction

  • About the Course
  • Learning Objectives
  • Approach
  • Audience
  • Minimum Hardware Requirements
  • Software Requirements
  • Conventions
  • Installation and Setup
2

Introduction to Data Wrangling with Python

  • Introduction
  • Python for Data Wrangling
  • Lists, Sets, Strings, Tuples, and Dictionaries
  • Summary
3

Advanced Data Structures and File Handling

  • Introduction
  • Advanced Data Structures
  • Basic File Operations in Python
  • Summary
4

Introduction to NumPy, Pandas, and Matplotlib

  • Introduction
  • NumPy Arrays
  • Pandas DataFrames
  • Statistics and Visualization with NumPy and Pandas
  • Summary
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
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
7

Learning the Hidden Secrets of Data Wrangling

  • Introduction
  • Advanced List Comprehension and the zip Function
  • Data Formatting
  • Identify and Clean Outliers
  • Summary
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
9

RDBMS and SQL

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

1

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
2

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
3

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
4

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
5

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
6

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
7

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
8

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
9

Application of Data Wrangling in Real Life

  • Skipping the First Row of the Data Set

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