6. Exploratory Data Analysis

• 6.1. Introduction
  • 6.1.1. Learning Goals
  • 6.1.2. Learning Objectives
  • 6.1.3. Reading List
• 6.2. Case Study 1: Exploratory Data Analysis
  • 6.2.1. Loading Data into a DataFrame from a CSV File
  • 6.2.2. Describing the Data
  • 6.2.3. Visualizing Distribution with Histograms
  • 6.2.4. Practice
  • 6.2.5. Scatter Plots for Discovering Relationships
  • 6.2.6. Power Tools: Scatter Matrix
  • 6.2.7. Developing Fluency
  • 6.2.8. Practice Questions
• 6.3. Case Study 1: Graphing Infant Mortality on a Map
  • 6.3.1. Using a Web API to get Country Codes
  • 6.3.2. Using a Web API on Your Own
• 6.4. Case Study 1: Screen Scraping the CIA
  • 6.4.1. Getting a List of All Fields
  • 6.4.2. Loading All the Data in Rough Form
  • 6.4.3. Cleaning the Data
  • 6.4.4. Saving the Data
  • 6.4.5. Comparing Across the Years
• 6.5. Case Study 1: Comparing Forms of Government
  • 6.5.1. Project
• 6.6. Case Study 2: Analyzing Protecting Minority Investors
  • 6.6.1. Loading Minority Investors Data into a DataFrame
  • 6.6.2. Describing Minority Investors
  • 6.6.3. Visualizing Minority Investors with a Histogram
  • 6.6.4. Discovering Relationships with Scatter Plots
  • 6.6.5. Minority Investors: Scatter Matrix
  • 6.6.6. Practice Questions
• 6.7. Case Study 2: Graphing Business Data on a Map
  • 6.7.1. Getting Country Codes from a Web API
• 6.8. Case Study 2: Scraping Business Data Using Panda and BeautifulSoup
  • 6.8.1. Getting a List of Business Fields
  • 6.8.2. Loading Business Data in Rough Form
  • 6.8.3. Cleaning Business Data
  • 6.8.4. Saving the Business Data
  • 6.8.5. Comparing Business Data Across the Years
• 6.9. Case Study 2: Comparing CIA Government Forms
  • 6.9.1. Project
• 6.10. Glossary
  • 6.10.1. Definitions
  • 6.10.2. Keywords

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