--- title: Data Visualization description: Data visualization focuses on communicating quantitative information through graphical representations. You will understand how to select appropriate chart types, apply design principles, and use visualization tools to make complex statistical findings accessible and actionable. category: programming-tech subcategory: data-science difficulty: beginner, intermediate, advanced url: /subject/data-visualization --- # Data Visualization Data visualization focuses on communicating quantitative information through graphical representations. You will understand how to select appropriate chart types, apply design principles, and use visualization tools to make complex statistical findings accessible and actionable. ## Available Resources 1 Videos • 5 Books • 5 Courses • 10 Websites ## Websites ### 1. Flourish Browser-based tool for building animated and interactive charts, maps and scrollytelling stories from spreadsheet data using preset templates, with no coding needed. Publishing and embedding are free on public projects. **Difficulty:** Beginner | **Price:** Free **Link:** https://flourish.studio/ **Tags:** flourish, interactive-charts, data-storytelling, no-code, scrollytelling ### 2. Datawrapper Web tool used widely in newsrooms to turn spreadsheet data into publication-quality charts, maps and tables. You paste data, pick a chart type, refine labels and colors, then embed the responsive result. **Difficulty:** Beginner | **Price:** Free **Link:** https://www.datawrapper.de/ **Tags:** datawrapper, charts, maps, newsroom-graphics, no-code ### 3. Observable A reactive JavaScript notebook platform for exploratory data work, where cells re-run automatically as inputs change. Useful for prototyping D3 and Plot visualizations, sharing runnable code, and studying published notebooks from the visualization community. **Difficulty:** Beginner | **Price:** Free **Link:** https://observablehq.com/ **Tags:** observable, javascript, d3, notebooks, interactive-visualization ### 4. Information is Beautiful David McCandless's gallery of hand-crafted infographics on science, culture and current affairs, with source datasets published alongside most pieces. Useful as a reference for composition and color choices, and for studying how claims map onto visual form. **Difficulty:** Beginner | **Price:** Free **Link:** https://informationisbeautiful.net/ **Tags:** infographics, information-design, visual-design, data-journalism, inspiration ### 5. dataviz.org Dataviz.org is the hub of the Data Visualization Society, offering resources and community for data visualization professionals and enthusiasts. It features articles, tutorials, case studies, events, and discussions to learn, showcase work, and connect with others in the field. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://dataviz.org **Tags:** websites, technology-computer-science, statistics-data-science ### 6. flowingdata.com FlowingData is a data visualization blog that teaches how to tell stories with data, featuring tutorials, design tips, case studies, and a gallery of real-world charts, dashboards, and infographics. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://flowingdata.com **Tags:** websites, technology-computer-science, data-science--ai ### 7. datavizcatalogue.com Data Viz Catalogue is a comprehensive, browsable library of data visualization types, offering clear definitions, use cases, and visual examples to help you select the right chart for your data. Each entry explains when to use the design, how it differs from similar visuals, and shows representative illustrations. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://datavizcatalogue.com **Tags:** websites, technology-computer-science, data-science ### 8. r-graph-gallery.com R Graph Gallery is a curated collection of data visualization examples built with R, featuring runnable code and explanations to reproduce and customize charts (primarily ggplot2). **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://r-graph-gallery.com **Tags:** websites, technology-computer-science, data-science--ai ### 9. data-to-viz.com Data-to-Viz is a practical reference and gallery of data visualization techniques, offering clear explanations of many chart types, best-use scenarios, and visual examples to illustrate effective data storytelling. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://data-to-viz.com **Tags:** websites, technology-computer-science, data-science--ai ### 10. Storytelling with Data **Author:** Cole Nussbaumer Knaflic Cole Nussbaumer Knaflic's site on communicating with data, with blog posts, makeover examples, a podcast and community challenges. It teaches how to choose effective charts, remove clutter, direct attention and build a clear narrative around quantitative findings for business audiences. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://storytellingwithdata.com **Tags:** data-storytelling, chart-design, data-communication, decluttering, presentation-design ## Videos ### 1. Data Visualization Full Course - Learn Data Visualization in 7 Hours A long-form Python course covering NumPy arrays, Pandas dataframes, and plotting with Matplotlib and Seaborn. Work through it to load, clean and summarize tabular datasets, then chart the results in code. **Difficulty:** Beginner | **Price:** Free **Link:** https://www.youtube.com/watch?v=r-uOLxNrNk8 **Tags:** python, matplotlib, seaborn, pandas, numpy ## Courses ### 1. Data Visualization with Python freeCodeCamp's certification track for building charts in the browser with D3.js, plus HTML and SVG basics and consuming JSON APIs. Completing the projects gives you a bar chart, scatterplot, heat map, choropleth and treemap. **Difficulty:** Beginner | **Price:** Free **Link:** https://www.freecodecamp.org/learn/data-visualization/ **Tags:** d3js, javascript, svg, web-charts, json-apis ### 2. Data Visualization Whether being used to customize advertising to millions of website visitors or streamline inventory ordering at a small restaurant, data is becoming more integral to success. Too often, we’re not sure how use data to find answers to the questions that will make us more successful in what we do. In this course, you will discover what data is and think about what questions you have that can be answered by the data – even if you’ve never thought about data before. Based on existing data, you will learn to develop a research question, describe the variables and their relationships, calculate basic statistics, and present your results clearly. By the end of the course, you will be able to use powerful data analysis tools – either SAS or Python – to manage and visualize your data, including how to deal with missing data, variable groups, and graphs. Throughout the course, you will share your progress with others to gain valuable feedback, while also learning how your peers use data to answer their own questions. **Difficulty:** Intermediate | **Price:** Free **Link:** https://www.coursera.org/learn/data-visualization **Tags:** data-visualization, visual-analytics, charts, data-communication, online-course ### 3. Data Visualization with Python Python plotting course covering Matplotlib, Seaborn, Folium, and Plotly/Dash. Labs build line, bar, area, histogram, pie, and scatter charts, plus choropleth maps and an interactive dashboard, ending in a project applying the libraries to a real dataset. **Difficulty:** Beginner | **Language:** English | **Duration:** 3 weeks of study, 4-5 hours/week | **Price:** Free **Link:** https://www.coursera.org/learn/python-for-data-visualization **Tags:** courses, technology-computer-science, technical-skills ### 4. Data Visualization **Author:** Aihua Li Ball State University course on visualizing large datasets in R across five modules. Covers exploratory analysis with ggplot2, histograms, scatter plots and box plots, colour choices, interactive and spatial maps, and R Markdown reports, ending with a build-your-own visualization project. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://www.coursera.org/learn/ball-state-university-data-visualization-open **Tags:** data-visualization, ggplot2, r-programming, exploratory-data-analysis, r-markdown ### 5. Advanced Data Visualization Part of HarvardX's Data Science series, this course teaches exploratory graphics in R with ggplot2: distributions, summary statistics, and the principles behind effective charts, using case studies that show how plots can mislead. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://www.edx.org/learn/data-visualization/harvard-university-data-science-visualization **Tags:** courses, technology-computer-science, data-science ## Podcasts ### 1. PolicyViz **Author:** Jon Schwabish Jon Schwabish interviews researchers, designers, and analysts about presenting data clearly, covering chart choice, color, annotation, and slide design. Episodes mix craft-level technique with the working habits organizations need to turn analysis into communication people actually read. **Difficulty:** Beginner | **Language:** en | **Price:** Free **Link:** https://policyviz.com/podcast/ **Tags:** data-communication, presentation-design, information-design, dataviz-interviews, charts ### 2. Data Viz Today **Author:** Alli Torban Short episodes in which designer Alli Torban breaks down a single visualization decision at a time: chart selection, annotation, color, layout, and process. She dissects published charts and interviews practitioners about how their pieces were built. **Difficulty:** Beginner | **Language:** en | **Price:** Free **Link:** https://dataviztoday.com/ **Tags:** information-design, dataviz-workflow, design-tools, charts, dataviz-interviews ## Books ### 1. Dashboards That Deliver: How to Design, Develop, and Deploy Dashboards That Work **Author:** Steve Wexler, Jeffrey Shaffer, Andy Cotgreave, Amanda Makulec Tool-agnostic guide to the full dashboard lifecycle: requirements gathering, discovery, prototyping, release and maintenance, with annotated real-world dashboards from healthcare, finance, marketing and transport. Readers learn to manage stakeholders and deliver dashboards that people actually use. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/1394281838?tag=edmonddante07-20 **Tags:** dashboard-design, data-visualization, requirements-gathering, prototyping, business-intelligence ### 2. The Visual Display of Quantitative Information **Author:** Edward R. Tufte Tufte's foundational treatise on statistical graphics, introducing data-ink ratio, chartjunk, and small multiples through historical examples like Minard's Napoleon map. It gives you criteria for judging whether a chart earns its ink. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/096139210X?tag=edmonddante07-20 **Tags:** books, technology-computer-science, data-science--ai ### 3. ggplot2 **Author:** Hadley Wickham Wickham's reference for the R plotting package built on the grammar of graphics, explaining layers, aesthetics, scales, facets and coordinate systems. After it you can compose complex statistical graphics from small, composable pieces rather than canned chart types. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/0387981403?tag=edmonddante07-20 **Tags:** books, technology-computer-science, statistics-data-science ### 4. Data Visualization: A Practical Introduction **Author:** Kieran Healy A social scientist's guide to making graphs in R with ggplot2, pairing perception research on why some charts mislead with worked code for cleaning, plotting, faceting and refining figures for publication. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/0691181624?tag=edmonddante07-20 **Tags:** books, technology-computer-science, data-science ### 5. Fundamentals of Data Visualization **Author:** Claus O. Wilke Wilke's tool-agnostic guide to figure design: choosing plot types for amounts, distributions, proportions and trends, using color deliberately, and avoiding common failures. It gives you a checklist for judging whether a figure communicates clearly. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/1492031089?tag=edmonddante07-20 **Tags:** books, technology-computer-science, data-science--ai --- *This content is part of Dantes.io - Your Treasure Map to Knowledge* *Curated by humans at Dantes.io. Personal study use welcome; republishing this curation requires permission (team@dantes.io).* View this page online: https://dantes.io/subject/data-visualization