From 741b3e588bf750a85f03e387562a2d30d5af0310 Mon Sep 17 00:00:00 2001 From: Garrett Date: Wed, 6 Apr 2016 14:20:52 -0400 Subject: [PATCH] Small edits to work.Rmd --- work.Rmd | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/work.Rmd b/work.Rmd index 9a539e3..8a82166 100644 --- a/work.Rmd +++ b/work.Rmd @@ -2,7 +2,7 @@ With data, the relationships between values matter as much as the values themselves. Tidy data encodes those relationships. -Throughout this book we work with "tibbles" instead of the traditional data frame. Tibbles _are_ data frame but encode some patterns that make modern usage of R better. Unfortunately R is an old language, and things that made sense 10 or 20 years a go are no longer as valid. It's difficult to change base R without breaking existing code, so most innovation occurs in packages, providing new functions that you should use instead of the old ones. +Throughout this book we work with "tibbles" instead of the traditional data frame. Tibbles _are_ data frames but they encode some patterns that make modern usage of R better. Unfortunately R is an old language, and things that made sense 10 or 20 years a go are no longer as valid. It's difficult to change base R without breaking existing code, so most innovation occurs in packages, providing new functions that you should use instead of the old ones. ```{r} library(tibble) @@ -16,7 +16,7 @@ The majority of the functions that you'll use in this book already produce tibbl as_data_frame(iris) ``` -As well as data frames, this function also knows how to convert lists (provided the elements are equal length vectors), matrices, and tables. +`as_data_frame()` knows how to convert data frames, lists (provided the elements are equal length vectors), matrices, and tables. You can also create a new tibble from individual vectors with `data_frame()`: