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.

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* Actual course outline may vary depending on offering center. Contact your sales representative for more information.

Learning Objectives

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.

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

Audience

Experienced data professionals will benefit from this course.

Language

English

Prerequisites

While there are no prerequisites for this course, please ensure you have the right level of experience to be successful in this training.

Length: 365.0 days ( hours)

Level:

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