基本信息

---

下载

   友情提示：（无需注册或充值，赞助后即可获取资源下载链接）

---

     嘿，亲！知识可是无价之宝呢，但咱这精心整理的资料也耗费了不少心血呀。小小地破费一下，绝对物超所值哦！如有下载和支付问题，请联系我们QQ(微信同号)：813200300

本次赞助数额为： 2 元　

支付宝支付

微信支付

   源码介绍

---

BRIEF CONTENTS
Acknowledgments
Introduction
Part I: Data Mining
Chapter 1: The Programming Languages You’ll Need to Know
Chapter 2: Where to Get Your Data
Chapter 3: Getting Data with Code
Chapter 4: Scraping Your Own Facebook Data
Chapter 5: Scraping a Live Site
Part II: Data Analysis
Chapter 6: Introduction to Data Analysis
Chapter 7: Visualizing Your Data
Chapter 8: Advanced Tools for Data Analysis
Chapter 9: Finding Trends in Reddit Data
Chapter 10: Measuring the Twitter Activity of Political Actors
Chapter 11: Where to Go from Here
Index
CONTENTS IN DETAIL
Acknowledgments
Introduction
What Is Data Analysis?
Who Is This Book For?
Conventions Used in This Book
What This Book Covers
Part I: Data Mining
Part II: Data Analysis
Downloading and Installing Python
Installing on Windows
Installing on macOS
Getting Help When You’re Stuck
Summary
PART I: DATA MINING
1
THE PROGRAMMING LANGUAGES YOU’LL NEED TO KNOW
Frontend Languages
How HTML Works
How CSS Works
How JavaScript Works
Backend Languages
Using Python
Getting Started with Python
Working with Numbers
Working with Strings
Storing Values in Variables
Storing Multiple Values in Lists
Working with Functions
Creating Your Own Functions
Using Loops
Using Conditionals
Summary
2
WHERE TO GET YOUR DATA
What Is an API?
Using an API to Get Data
Getting a YouTube API Key
Retrieving JSON Objects Using Your Credentials
Answering a Research Question Using Data
Refining the Data That Your API Returns
Summary
3
GETTING DATA WITH CODE
Writing Your First Script
Running a Script
Planning Out a Script
Libraries and pip
Creating a URL-based API Call
Storing Data in a Spreadsheet
Converting JSON into a Dictionary
Going Back to the Script
Running the Finished Script
Dealing with API Pagination
Templates: How to Make Your Code Reusable
Storing Values That Change in Variables
Storing Code in a Reusable Function
Summary
4
SCRAPING YOUR OWN FACEBOOK DATA
Your Data Sources
Downloading Your Facebook Data
Reviewing the Data and Inspecting the Code
Structuring Information as Data
Scraping Automatically
Analyzing HTML Code to Recognize Patterns
Grabbing the Elements You Need
Extracting the Contents
Writing Data into a Spreadsheet
Building Your Rows List
Writing to Your .csv File
Running the Script
Summary
5
SCRAPING A LIVE SITE
Messy Data
Ethical Considerations for Data Scraping
The Robots Exclusion Protocol
The Terms of Service
Technical Considerations for Data Scraping
Reasons for Scraping Data
Scraping from a Live Website
Analyzing the Page’s Contents
Storing the Page Content in Variables
Making the Script Reusable
Practicing Polite Scraping
Summary
PART II: DATA ANALYSIS
6
INTRODUCTION TO DATA ANALYSIS
The Process of Data Analysis
Bot Spotting
Getting Started with Google Sheets
Modifying and Formatting the Data
Aggregating the Data
Using Pivot Tables to Summarize Data
Using Formulas to Do Math
Sorting and Filtering the Data
Merging Data Sets
Other Ways to Use Google Sheets
Summary
7
VISUALIZING YOUR DATA
Understanding Our Bot Through Charts
Choosing a Chart
Specifying a Time Period
Making a Chart
Conditional Formatting
Single-Color Formatting
Color Scale Formatting
Summary
8
ADVANCED TOOLS FOR DATA ANALYSIS
Using Jupyter Notebook
Setting Up a Virtual Environment
Organizing the Notebook
Installing Jupyter and Creating Your First Notebook
Working with Cells
What Is pandas?
Working with Series and Data Frames
Reading and Exploring Large Data Files
Looking at the Data
Viewing Specific Columns and Rows
Summary
9
FINDING TRENDS IN REDDIT DATA
Clarifying Our Research Objective
Outlining a Method
Narrowing the Data’s Scope
Selecting Data from Specific Columns
Handling Null Values
Classifying the Data
Summarizing the Data
Sorting the Data
Describing the Data
Summary
10
MEASURING THE TWITTER ACTIVITY OF POLITICAL ACTORS
Getting Started
Setting Up Your Environment
Loading the Data into Your Notebook
Lambdas
Filtering the Data Set
Formatting the Data as datetimes
Resampling the Data
Plotting the Data
Summary
11
WHERE TO GO FROM HERE
Coding Styles
Statistical Analysis
Other Kinds of Analyses
Conclusion
Index