Author: Kevin Feasel

Ian at Fells Stats wants to make a long-running Shiny app a bit more user-friendly:

Shiny operates in a reactive programming framework. Fundamentally this means that any time any UI element that affects the result changes, so does the result. This happens automatically, with your analysis code running every time a widget is changed. In a lot of cases, this is exactly what you want and it makes Shiny programs concise and easy to make; however in the case of long running processes, this can lead to frozen UI elements and a frustrating user experience.

The easiest solution is to use an Action Button and only run the analysis code when the action button is clicked. Another important component is to provide your user with feedback as to how long the analysis is going to take. Shiny has nice built in progress indicators that allow you to do this.

There are a couple of false starts in there but by the time you reach the third act, the story makes sense.  H/T R-Bloggers

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Dave Mason continues his journey toward learning R.  He looks next at the class() function:

Note the value assigned to horse_power is a whole number (integer) and the value assigned to miles_per_gallon is a rational number. But R tells us they are both of the “numeric” class. R does have an integer class. A variable’s class will be an integer if the value is followed by a capital “L”. Let’s reassign a value to horse_power to demonstrate:

> horse_power <- 240L
> class(horse_power)
[1] "integer"

Another way to determine the class of a variable is to use one of the is.*() functions. For example, is.integer() and is.numeric() tell us the miles_per_gallon is not an integer, and is a numeric:

> is.integer(miles_per_gallon)
[1] FALSE
> is.numeric(miles_per_gallon)
[1] TRUE

There’s also the typeof() function and the mode() function, and all three can differ under certain circumstances.

Next up, Dave hits vectors, the simplest of the interesting data types in R:

It’s important to know that the elements of a vector must be of the same class (data type). If the values passed to the c() function are of different classes, some of them will be coerced to a different class to ensure all classes of the vector are the same. Below, the parameter classes passed to the c() function include character, numeric, and integer. The corresponding numeric and integer parameter values are coerced to character within the vector:

> some_data <- c("a", "b", 7.5, 25L)
> some_data
[1] "a"   "b"   "7.5" "25" 
>

Read on for more about vectors.

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