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It’s a very simply function, but nonetheless very useful. Finally this is passed to ggplot() which creates histograms with geom_histogram(), and facets them into six panes with facet_wrap().map_df() essentially does a bind_rows() and outputs a single dataframe, adding a new variable dist which takes the names of the elements of the list, outputting a long dataframe.x) will convert each of these vectors of variables into a dataframe, naming the column of variables as x. Passing this to map_df() with the function (.First I create a list of six univariate normal distributions using rnorm().id = "dist" ) %>% ggplot + aes ( x = x, fill = dist ) + geom_histogram () + facet_wrap ( ~ dist, ncol = 2 ) Here’s a simple example: library ( dplyr ) library ( purrr ) library ( ggplot2 ) # See ?accumulate for my inspiration for this example rerun ( 6, rnorm ( 100 )) %>% map_df ( ~ data_frame ( x =. It also allows us to specify additional columns for our final dataframe which takes the names of the elements of the list.
Map() is a great function and one of its incarnations that I really like is map_df().This will apply a function to elements of a list, and then bind the dataframes together (assuming they can be combined). I’m using Hadley’s purrr package more and more, and its beginning to change the way I program in R, much like dplyr did.