dplyr 0.7.0 with great improvements for programming

Dplyr 0.7.0 has been published. One of the greatest improvements is the enhancement for standard evaluation.

Let’s look at an example. Let’s say I want to apply a function to a column of a data.frame. But the name of the data.frame can change from call to call. So the actual column is the value of a string.

Earlier to dplyr 0.7.0 I used the following methods using lazyeval:

Using geom_ribbon() to visualize a corridor for your data

Let’s say you have some data like this 1 2 3 4 5 set.seed(42) data <- data.frame( x = seq(1,30), y = 0.3 * seq(1,30) + 2 * rnorm(30) ) So let’s plot it using ggplot: 1 2 library(ggplot2) ggplot(data, aes(x=x, y=y)) + geom_point() + geom_line() Plotting an aim-corridor If this is something like your revenue, pageviews or something like that you may ask: “Is this good or is this bad?