Data Wrangling with Python
(DATA-WRGLG-PYTHON.AJ1) / ISBN : 978-1-64459-302-8
Über diesen Kurs
Nutzen Sie den Kurs und das Labor „Data Wrangling mit Python“, um ein Verständnis der damit verbundenen Konzepte und Methoden zu erlangen. Der Kurs und das Labor zum Thema Data Wrangling vermitteln ein Verständnis der verwendeten Prozesse sowie Kenntnisse über die gängigsten Tools und Techniken in diesem Bereich. Der Python-Kurs und das Labor zeigen auch, wie man das Python-Backend verwendet und Daten aus einer Reihe von Quellen, einschließlich dem Internet, extrahiert/transformiert.
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Unterricht
10+ Unterricht | 11+ Übungen | 72+ Tests | 84+ Karteikarten | 84+ Glossar der Begriffe
Testvorbereitung
47+ Fragen vor der Beurteilung | 53+ Fragen nach der Bewertung |
Praktische Übungen
45+ LiveLab | 6+ Videoanleitungen | 07+ Minutes
Videolektionen
33+ Videos | 03:13+ Hours
Introduction
- About the Course
- Learning Objectives
- Approach
- Audience
- Minimum Hardware Requirements
- Software Requirements
- Conventions
- Installation and Setup
Introduction to Data Wrangling with Python
- Introduction
- Python for Data Wrangling
- Lists, Sets, Strings, Tuples, and Dictionaries
- Summary
Advanced Data Structures and File Handling
- Introduction
- Advanced Data Structures
- Basic File Operations in Python
- Summary
Introduction to NumPy, Pandas, and Matplotlib
- Introduction
- NumPy Arrays
- Pandas DataFrames
- Statistics and Visualization with NumPy and Pandas
- Summary
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
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
Learning the Hidden Secrets of Data Wrangling
- Introduction
- Advanced List Comprehension and the zip Function
- Data Formatting
- Identify and Clean Outliers
- Summary
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
RDBMS and SQL
- Introduction
- Refresher of RDBMS and SQL
- Using an RDBMS (MySQL/PostgreSQL/SQLite)
- Reading Data from a Database in SQLite
- Summary
Application of Data Wrangling in Real Life
- Introduction
- Applying Your Knowledge to a Real-life Data Wrangling Task
- An Extension to Data Wrangling
- Summary
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