Collegare scatter plot

In questo esercizio userai plotly e crosstalk per collegare uno scatter plot dell’Housing Price Index (HPI) statunitense del 2017 rispetto alla percentuale di proprietari di casa a uno scatter plot dell’HPI 2017 rispetto al tasso di occupazione. Entrambi i pacchetti sono già stati caricati e i dati sono salvati in us2017.

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Visualizzazione interattiva dei dati intermedia con plotly in R

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# Create a SharedData object from us2017
shared_us <- ___(___)

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Questo esercizio fa parte del corso

Visualizzazione interattiva dei dati intermedia con plotly in R

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A review of key plotly commands. You will review how to create multiple plot types in plotly and how to polish your charts. Additionally, you will create static versions of the bubble and line charts that you will animate in the next chapter.

Exercise 1: Interactive and dynamic graphics Exercise 2: Which is the interactive graphic?Exercise 3: A simple time series plot Exercise 4: A simple scatterplot Exercise 5: Adding aesthetics to represent a variable Exercise 6: Color and size Exercise 7: Plotting symbols Exercise 8: Polishing your graphics Exercise 9: Moving Beyond Simple Interactivity Exercise 10: Bubble charts Exercise 11: Many time series

In this chapter, you will learn how to implement keyframe animation in plotly. You will explore how to create animations, such as Hans Rosling's bubble charts, as well as cumulative animations, such as an animation of a stock's valuation over time.

Exercise 1: Introduction to animated graphics Exercise 2: What's the frame?Exercise 3: Why do we need ids?Exercise 4: Animating a scatterplot Exercise 5: Factors as frames Exercise 6: Polishing animations Exercise 7: Polishing your regional animation Exercise 8: Polishing your HPI animation Exercise 9: Layering in plotly Exercise 10: Adding background text Exercise 11: Plotting the baseline Exercise 12: Cumulative animations Exercise 13: How many rows?Exercise 14: Median life expectancies Exercise 15: Animating median life expectancies

When you are exploring unexpected structure in your graphics, it's useful to have selections made on one chart update the other. For example, if you are exploring clusters observed on a scatterplot, it is useful to have the selected cluster update some chart of group membership, such as a jittered scatterplot or sets of bar charts. In this chapter, you will learn how to link your plotly charts to enable linked brushing. Along the way, you will also learn how to add dropdown menus, checkboxes, and sliders to your plotly charts, without the need for Shiny.

Exercise 1: Collegare due grafici Exercise 2: Oggetti sharedData Exercise 3: Collegare scatter plot

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Exercise 4: Grafici con highlighting()Exercise 5: Selezionare gruppi con il brushing Exercise 6: Evidenziare dati di serie storiche Exercise 7: Collegare un dotplot e un grafico di serie temporale Exercise 8: Collegare un grafico a barre a uno scatterplot Exercise 9: Strategie di selezione Exercise 10: Alla ricerca di cluster Exercise 11: Aggiungere menu a discesa Exercise 12: Rendere i grafici ancora più brillanti Exercise 13: Disporre le viste con bscols()Exercise 14: Aggiungere checkbox Exercise 15: Aggiungere uno slider

In the final chapter, you will use your expanded plotly toolkit to explore orbital space launches between 1957 and 2018. Along the way, you'll learn how to wrangle data to enable cumulative animations without common starting points, and hone your understanding of the crosstalk package.

Exercise 1: Introduction to the space launches data Exercise 2: Launches over time Exercise 3: Space race timeline Exercise 4: State vs. private launches Exercise 5: Recap: Animation Exercise 6: Animating the space race Exercise 7: Animating the private space race Exercise 8: Recap: linked views and selector widgets Exercise 9: Linking for group selection Exercise 10: Linked brushing Exercise 11: Linked views for summarization Exercise 12: Adding a slider for time Exercise 13: Wrap-up