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Adding a slider

A slider filter allows you to easily update the data values plotted by restricting a numeric variable to a specific range. In this exercise, your task is to include two slider filters for the scatterplot of the housing price index against homeownership in 2017: one for each axis.

plotly and crosstalk have already been loaded for you, and the data are stored in us2017.

Note: You may need to scroll down on or pop out the HTML Viewer to see the sliders.

Cet exercice fait partie du cours

Intermediate Interactive Data Visualization with plotly in R

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Instructions

  • Place two slider filters below the scatterplot stored in p17. The first slider should correspond to the housing price index (house_price), and the second slider should correspond to the percentage of home ownership (home_owners).
  • Add slider labels that match the axis titles in p17, "HPI" and "Home ownership (%)".

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

shared_us <- SharedData$new(us2017)
p17 <- shared_us %>%
  plot_ly(x = ~home_owners, y = ~house_price, 
          color = ~region, height = 400) %>%
  add_markers() %>%
  layout(xaxis = list(title = "Home ownership (%)"), 
         yaxis = list(title = "HPI"))
  
# add a slider filter for each axis below the scatterplot
___(
  ___(p17,
      ___(id = "price",  label = ___,  sharedData = ___,  column = ___),
      ___(id = "owners",  label = ___,  sharedData = ___, column = ___)
  )
)
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