Data Wrangling with Python
(DATA-WRGLG-PYTHON.AJ1)
/ ISBN: 978-1-64459-302-8
This course includes
Lessons
TestPrep
LiveLab
Mentoring (Add-on)
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.
Lessons
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10+ Lessons
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11+ Exercises
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72+ Quizzes
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84+ Flashcards
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84+ Glossary of terms
TestPrep
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47+ Pre Assessment Questions
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53+ Post Assessment Questions
LiveLab
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45+ LiveLab
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6+ Video tutorials
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07+ Minutes
Video Lessons
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33+ Videos
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03:13+ Hours
- About the Course
- Learning Objectives
- Approach
- Audience
- Minimum Hardware Requirements
- Software Requirements
- Conventions
- Installation and Setup
- Introduction
- Python for Data Wrangling
- Lists, Sets, Strings, Tuples, and Dictionaries
- Summary
- Introduction
- Advanced Data Structures
- Basic File Operations in Python
- Summary
- Introduction
- NumPy Arrays
- Pandas DataFrames
- Statistics and Visualization with NumPy and Pandas
- Summary
- Introduction
- Subsetting, Filtering, and Grouping
- Detecting Outliers and Handling Missing Values
- Concatenating, Merging, and Joining
- Useful Methods of Pandas
- Summary
- Introduction
- Reading Data from Different Text-Based (and Non-Text-Based) Sources
- Introduction to Beautiful Soup 4 and Web Page Parsing
- Summary
- Introduction
- Advanced List Comprehension and the zip Function
- Data Formatting
- Identify and Clean Outliers
- Summary
- 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
- Introduction
- Refresher of RDBMS and SQL
- Using an RDBMS (MySQL/PostgreSQL/SQLite)
- Reading Data from a Database in SQLite
- Summary
- Introduction
- Applying Your Knowledge to a Real-life Data Wrangling Task
- An Extension to Data Wrangling
- Summary
Hands on Activities (Live Labs)
- Sorting a List
- Generating a List
- Deleting a Value from a Dictionary
- Accessing and Setting Values in a Dictionary
- Slicing a String
- Implementing a Queue
- Splitting a String
- Implementing Multi-Element Membership Checking
- Implementing a Stack
- Opening a File and Printing its Content
- Generating Arrays Using arange and linspace
- Multiplying Two Arrays
- Adding Two NumPy Arrays
- Creating a NumPy Array
- Filtering Elements from a Matrix
- Stacking Arrays
- Subsetting a DataFrame
- Grouping a DataFrame
- Dropping the Missing Values
- Replacing Missing Values in a DataFrame
- Joining DataFrames
- Concatenating Data Frames
- Counting Values
- Bypassing the Headers of a CSV File
- Reading Data from a CSV File
- Stacking URLs from a Document Using bs4
- Counting Tags
- Using the zip Function
- Using a One-Liner Generator Expression
- Using a Generator Expression
- Using the format Function
- Using a Box Plot
- 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
- Deleting the Data
- Using Joins
- Using the Foreign Key
- Updating Data
- Using the ORDER BY Clause
- Using the SELECT Statement
- Using the SELECT Statement
- Skipping the First Row of the Data Set
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