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hadley 2016-10-03 07:37:45 -05:00
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@ -76,7 +76,7 @@ However, we strongly believe that it's best to master one tool at a time. You wi
### Non-rectangular data
This book focuses exclusively on rectangular data: collections of values that are each associated with a variable and an observation. There are lots of datasets that do not naturally fit in this paradigm: images, sounds, trees, text. But rectangular data frames are extremely common in science and in industry and we believe that they're a great place to start your data science journey.
This book focuses exclusively on rectangular data: collections of values that are each associated with a variable and an observation. There are lots of datasets that do not naturally fit in this paradigm: including images, sounds, trees, and text. But rectangular data frames are extremely common in science and industry, and we believe that they're a great place to start your data science journey.
### Hypothesis confirmation
@ -108,7 +108,7 @@ To run the code in this book, you will need to install both R and the RStudio ID
### RStudio
RStudio is an integrated development environment, or IDE, for R programming. When you get started, there two key regions in the interface:
RStudio is an integrated development environment, or IDE, for R programming. When you get started, there are two key regions in the interface:
```{r echo = FALSE, out.width = "75%"}
knitr::include_graphics("diagrams/rstudio-console.png")
@ -154,11 +154,11 @@ Throughout the book we use a consistent set of conventions to refer to code:
* If we want to make it clear what package an object comes from, we'll use
the package name followed by two colons, like `dplyr::mutate()`, or
`nycflights13::flights`. This is valid R code.
`nycflights13::flights`. This is also valid R code.
## Getting help and learning more
This book is not an island; there is no single resource that will allow you to master R. As you start to apply the techniques described in this book to your own data you will soon find questions that I do not answer. This section describes a few tips to help you get help, and to help you keep learning.
This book is not an island; there is no single resource that will allow you to master R. As you start to apply the techniques described in this book to your own data you will soon find questions that I do not answer. This section describes a few tips on how to get help, and to help you keep learning.
If you get stuck, start with Google. Typically adding "R" to a query is enough to restrict it to relevant results: if the search isn't useful, it often means that there aren't any R-specific results available. Google is particularly useful for error messages. If you get an error message and you have no idea what it means, try googling it! Chances are that someone else has been confused by it in the past, and there will be help somewhere on the web. (If the error message isn't in English, run `Sys.setenv(LANGUAGE = "en")` and re-run the code; you're more likely to find help for English error messages.)