From b3aa1ff9e790489a202698c04a39c22743ce0825 Mon Sep 17 00:00:00 2001 From: S'busiso Mkhondwane Date: Fri, 12 Aug 2016 22:04:31 +0200 Subject: [PATCH] Update tibble.Rmd (#249) Typo --- tibble.Rmd | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/tibble.Rmd b/tibble.Rmd index 4d942ad..dd1815e 100644 --- a/tibble.Rmd +++ b/tibble.Rmd @@ -67,7 +67,7 @@ I often add a comment (the line starting with `#`), to make it really clear wher ## Tibbles vs. data frames -There are two main differences in the usage of a data frame vs a tibble: printing, and subsetting. +There are two main differences in the usage of a data frame vs a tibble: printing and subsetting. ### Printing @@ -83,7 +83,7 @@ tibble( ) ``` -Tibbles are designed so that you don't accidentally overwhelm your console when you print large dataframes. But sometimes you need more output than the default display. There are a few options that can help. +Tibbles are designed so that you don't accidentally overwhelm your console when you print large data frames. But sometimes you need more output than the default display. There are a few options that can help. First, you can explicitly `print()` the data frame and control the number of rows (`n`) and the `width` of the display. `width = Inf` will display all columns: @@ -112,7 +112,7 @@ nycflights13::flights %>% ### Subsetting -So far all the tools you've learned have worked with complete dataframes. If you want to pull out a single variable, you need some new tools, `$` and `[[`. `[[` can extract by name or position; `$` only extracts by name but is a little less typing. +So far all the tools you've learned have worked with complete data frames. If you want to pull out a single variable, you need some new tools, `$` and `[[`. `[[` can extract by name or position; `$` only extracts by name but is a little less typing. ```{r} df <- tibble(