Further Reading: Plotly Graph Objects

Tier 1: Essential Reading

Plotly Python Graph Objects Documentation. plotly.com/python/graph-objects/ The official documentation for Graph Objects, organized by trace type and layout feature. The best starting point for specific API questions.

Plotly Figure Reference. plotly.com/python/reference/ The complete JSON schema for every Plotly trace and layout property. If you need to know the exact name and type of a property, this is where to look. Indispensable for Graph Objects work.

Plotly Subplots Tutorial. plotly.com/python/subplots/ The tutorial on make_subplots, covering shared axes, mixed types, secondary y-axes, and row/column spans. Read once to understand the capabilities.

Silver, Nate. The Signal and the Noise. Penguin Press, 2012. Silver's book on forecasting and probability, written before the FiveThirtyEight election dashboards of 2016 and 2020 but laying out the philosophy behind them. Essential context for Case Study 2.

Kay, Matthew, and Jeffrey Heer. "Beyond Weber's Law: A Second Look at Ranking Visualizations of Correlation." IEEE Transactions on Visualization and Computer Graphics 22, no. 1 (2016): 469-478. A research paper on how people perceive correlation from scatter plots — relevant when you build dual-y-axis charts (which appear to show correlation but do not).

Few, Stephen. Information Dashboard Design. 2nd ed. Analytics Press, 2013. The seminal book on dashboard design, covering information density, chart selection, and interaction design. Read for the theoretical foundation of the Bloomberg (Case Study 1) and FiveThirtyEight (Case Study 2) approaches.

Tufte, Edward R. Envisioning Information. Graphics Press, 1990. Tufte's chapter on "small multiples" and his arguments for high information density inform the case study's discussion of dense charts for specialist audiences.

Plotly Dash Documentation. dash.plotly.com The official documentation for Dash, Plotly's web framework for building full interactive applications. If you want to move beyond single figures to full dashboards, Dash is the next step. Covered in Chapter 30.

Tier 3: Tools and Online Resources

Resource URL / Source Description
Plotly Python GitHub github.com/plotly/plotly.py The Plotly Python source code. Useful for understanding how Graph Objects constructs figures internally.
plotly.js GitHub github.com/plotly/plotly.js The JavaScript library that actually renders Plotly charts. Browse to understand what Python generates under the hood.
Plotly Dashboards gallery plotly.com/examples/ A gallery of Plotly-based dashboards and visualizations for inspiration and reference.
Plotly community forum community.plotly.com Active user forum with thousands of questions and answers on Graph Objects specifics.
d3-format reference github.com/d3/d3-format The format-string specification that Plotly uses for axis tick formatting.
d3-time-format reference github.com/d3/d3-time-format The time-format strings used for date axes.
Bloomberg Terminal overview bloomberg.com/professional/solution/bloomberg-terminal/ The official marketing page for the Terminal. Useful for understanding what the product does and why it commands the prices it does.
FiveThirtyEight historical forecasts projects.fivethirtyeight.com/2020-election-forecast/ The live FiveThirtyEight 2020 election dashboard is still available as an archived page. Good for inspection and as a design reference.
The Pudding pudding.cool A data journalism publication known for elaborate scrollable dashboards. Inspiration for Plotly-scale interactive work.

A note on reading order: If you want one additional source, skim the Plotly Figure Reference (plotly.com/python/reference). You do not need to read it cover to cover — use it as a lookup when you have a specific property question. For conceptual depth, Few's Information Dashboard Design is the best single book on the design side. For the debugging skill of inspecting JSON specs, the best teacher is experience — spend an hour poking at fig.to_dict() on figures you have built, and the mental model will click.