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Data Wrangling with Python

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.
Test Prep
47+ Pre Assessment Questions | 53+ Post Assessment Questions |
45+ LiveLab | 6+ Video tutorials | 07+ Minutes
33+ Videos | 03:13+ Hours

Why choose TOPTALENT?


Lessons 1:

  • 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:

  • 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