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Döbler, Mario. The data visualization workshop: a self-paced, practical approach to transforming your complex data into compelling, captivating graphics. — Third edition. — 1 online resource — <URL:http://elib.fa.ru/ebsco/2548565.pdf>.

Дата создания записи: 06.08.2020

Тематика: Information visualization — Computer programs.; Python (Computer program language); Python (Computer program language)

Коллекции: EBSCO

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Оглавление

  • Cover
  • FM
  • Copyright
  • Table of Contents
  • Preface
  • Chapter 1: The Importance of Data Visualization and Data Exploration
    • Introduction
      • Introduction to Data Visualization
      • The Importance of Data Visualization
      • Data Wrangling
      • Tools and Libraries for Visualization
    • Overview of Statistics
      • Measures of Central Tendency
      • Measures of Dispersion
      • Correlation
      • Types of Data
      • Summary Statistics
    • NumPy
      • Exercise 1.01: Loading a Sample Dataset and Calculating the Mean Using NumPy
      • Activity 1.01: Using NumPy to Compute the Mean, Median, Variance, and Standard Deviation of a Dataset
      • Basic NumPy Operations
        • Indexing
        • Slicing
        • Splitting
        • Iterating
      • Exercise 1.02: Indexing, Slicing, Splitting, and Iterating
      • Advanced NumPy Operations
        • Filtering
        • Sorting
        • Combining
        • Reshaping
      • Exercise 1.03: Filtering, Sorting, Combining, and Reshaping
    • pandas
      • Advantages of pandas over NumPy
      • Disadvantages of pandas
      • Exercise 1.04 Loading a Sample Dataset and Calculating the Mean using Pandas
      • Exercise 1.05: Using pandas to Compute the Mean, Median, and Variance of a Dataset
      • Basic Operations of pandas
        • Indexing
        • Slicing
        • Iterating
        • Series
      • Exercise 1.06: Indexing, Slicing, and Iterating Using pandas
      • Advanced pandas Operations
        • Filtering
        • Sorting
        • Reshaping
      • Exercise 1.07: Filtering, Sorting, and Reshaping
      • Activity 1.02: Forest Fire Size and Temperature Analysis
    • Summary
  • Chapter 2: All You Need to Know about Plots
    • Introduction
    • Comparison Plots
      • Line Chart
        • Uses
        • Example
        • Design Practices
      • Bar Chart
        • Use
        • Don’ts of Bar Charts
        • Examples
        • Design Practices
      • Radar Chart
        • Uses
        • Examples
        • Design Practices
      • Activity 2.01: Employee Skill Comparison
    • Relation Plots
      • Scatter Plot
        • Uses
        • Examples
        • Design Practices
        • Variants: Scatter Plots with Marginal Histograms
        • Examples
      • Bubble Plot
        • Use
        • Example
        • Design Practices
      • Correlogram
        • Examples
        • Design Practices
      • Heatmap
        • Use
        • Examples
        • Design Practice
      • Activity 2.02: Road Accidents Occurring over Two Decades
    • Composition Plots
      • Pie Chart
        • Use
        • Examples
        • Design Practices
        • Variants: Donut Chart
        • Design Practice
      • Stacked Bar Chart
        • Use
        • Examples
        • Design Practices
      • Stacked Area Chart
        • Use
        • Examples
        • Design Practice
      • Activity 2.03: Smartphone Sales Units
      • Venn Diagram
        • Use
        • Example
        • Design Practice
    • Distribution Plots
      • Histogram
        • Use
        • Example
        • Design Practice
      • Density Plot
        • Use
        • Example
        • Design Practice
      • Box Plot
        • Use
        • Examples
      • Violin Plot
        • Use
        • Examples
        • Design Practice
      • Activity 2.04: Frequency of Trains during Different Time Intervals
    • Geoplots
      • Dot Map
        • Use
        • Example
        • Design Practices
      • Choropleth Map
        • Use
        • Example
        • Design Practices
      • Connection Map
        • Use
        • Examples
        • Design Practices
    • What Makes a Good Visualization?
      • Common Design Practices
      • Activity 2.05: Analyzing Visualizations
      • Activity 2.06: Choosing a Suitable Visualization
    • Summary
  • Chapter 3: A Deep Dive into Matplotlib
    • Introduction
    • Overview of Plots in Matplotlib
    • Pyplot Basics
      • Creating Figures
      • Closing Figures
      • Format Strings
      • Plotting
      • Plotting Using pandas DataFrames
      • Ticks
      • Displaying Figures
      • Saving Figures
      • Exercise 3.01: Creating a Simple Visualization
    • Basic Text and Legend Functions
      • Labels
      • Titles
      • Text
      • Annotations
      • Legends
      • Activity 3.01: Visualizing Stock Trends by Using a Line Plot
    • Basic Plots
      • Bar Chart
      • Activity 3.02: Creating a Bar Plot for Movie Comparison
      • Pie Chart
      • Exercise 3.02: Creating a Pie Chart for Water Usage
      • Stacked Bar Chart
      • Activity 3.03: Creating a Stacked Bar Plot to Visualize Restaurant Performance
      • Stacked Area Chart
      • Activity 3.04: Comparing Smartphone Sales Units Using a Stacked Area Chart
      • Histogram
      • Box Plot
      • Activity 3.05: Using a Histogram and a Box Plot to Visualize Intelligence Quotient
      • Scatter Plot
      • Exercise 3.03: Using a Scatter Plot to Visualize Correlation between Various Animals
      • Bubble Plot
    • Layouts
      • Subplots
      • Tight Layout
      • Radar Charts
      • Exercise 3.04: Working on Radar Charts
      • GridSpec
      • Activity 3.06: Creating a Scatter Plot with Marginal Histograms
    • Images
      • Basic Image Operations
      • Activity 3.07: Plotting Multiple Images in a Grid
    • Writing Mathematical Expressions
    • Summary
  • Chapter 4: Simplifying Visualizations Using Seaborn
    • Introduction
      • Advantages of Seaborn
    • Controlling Figure Aesthetics
      • Seaborn Figure Styles
      • Removing Axes Spines
      • Controlling the Scale of Plot Elements
      • Exercise 4.01: Comparing IQ Scores for Different Test Groups by Using a Box Plot
    • Color Palettes
      • Categorical Color Palettes
      • Sequential Color Palettes
      • Diverging Color Palettes
      • Exercise 4.02: Surface Temperature Analysis
      • Activity 4.01: Using Heatmaps to Find Patterns in Flight Passengers' Data
    • Advanced Plots in Seaborn
      • Bar Plots
      • Activity 4.02: Movie Comparison Revisited
      • Kernel Density Estimation
      • Plotting Bivariate Distributions
      • Visualizing Pairwise Relationships
      • Violin Plots
      • Activity 4.03: Comparing IQ Scores for Different Test Groups by Using a Violin Plot
    • Multi-Plots in Seaborn
      • FacetGrid
      • Activity 4.04: Visualizing the Top 30 Music YouTube Channels Using Seaborn's FacetGrid
    • Regression Plots
      • Activity 4.05: Linear Regression for Animal Attribute Relations
    • Squarify
      • Exercise 4.03: Water Usage Revisited
      • Activity 4.06: Visualizing the Impact of Education on Annual Salary and Weekly Working Hours
    • Summary
  • Chapter 5: Plotting Geospatial Data
    • Introduction
      • The Design Principles of geoplotlib
    • Geospatial Visualizations
      • Voronoi Tessellation
      • Delaunay Triangulation
      • Choropleth Plot
      • Exercise 5.01: Plotting Poaching Density Using Dot Density and Histograms
      • Activity 5.01: Plotting Geospatial Data on a Map
      • The GeoJSON Format
      • Exercise 5.02: Creating a Choropleth Plot with GeoJSON Data
    • Tile Providers
      • Exercise 5.03: Visually Comparing Different Tile Providers
    • Custom Layers
      • Exercise 5.04: Plotting the Movement of an Aircraft with a Custom Layer
      • Activity 5.02: Visualizing City Density by the First Letter Using an Interactive Custom Layer
    • Summary
  • Chapter 6: Making Things Interactive with Bokeh
    • Introduction
      • Concepts of Bokeh
      • Interfaces in Bokeh
      • Output
      • Bokeh Server
      • Presentation
      • Integrating
    • Basic Plotting
      • Exercise 6.01: Plotting with Bokeh
      • Exercise 6.02: Comparing the Plotting and Models Interfaces
      • Activity 6.01: Plotting Mean Car Prices of Manufacturers
    • Adding Widgets
      • Exercise 6.03: Building a Simple Plot Using Basic Interactivity Widgets
      • Exercise 6.04: Plotting Stock Price Data in Tabs
      • Activity 6.02: Extending Plots with Widgets
    • Summary
  • Chapter 7: Combining What We Have Learned
    • Introduction
      • Activity 7.01: Implementing Matplotlib and Seaborn on the New York City Database
      • Bokeh
      • Activity 7.02: Visualizing Stock Prices with Bokeh
      • Geoplotlib
      • Activity 7.03: Analyzing Airbnb Data with Geoplotlib
    • Summary
  • Appendix
  • Index

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