From 9173b3db60c351690d58296ebc86975bb055a895 Mon Sep 17 00:00:00 2001 From: Stephan Koenig Date: Wed, 4 Jan 2023 18:21:34 -0800 Subject: [PATCH] Fix typos in chapters Whole game, Data visualization, Numbers (#1215) * Fix typo Fixes #1208 * Fix typo Fixes #1207 * Fix typo --- data-visualize.qmd | 2 +- numbers.qmd | 2 +- whole-game.qmd | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/data-visualize.qmd b/data-visualize.qmd index 9ec4972..2ce3218 100644 --- a/data-visualize.qmd +++ b/data-visualize.qmd @@ -268,7 +268,7 @@ ggplot( geom_smooth() ``` -We have successfully added a smooth curves, but this plot doesn't look like the plot from @sec-ultimate-goal, which only has one curve for the entire dataset as opposed to separate curves for each of the penguin species. +We have successfully added smooth curves, but this plot doesn't look like the plot from @sec-ultimate-goal, which only has one curve for the entire dataset as opposed to separate curves for each of the penguin species. When aesthetic mappings are defined in `ggplot()`, at the *global* level, they're inherited by each of the subsequent geom layers of the plot. However, each geom function in ggplot2 can also take a `mapping` argument, which allows for aesthetic mappings at the *local* level. diff --git a/numbers.qmd b/numbers.qmd index 70bb66b..8793013 100644 --- a/numbers.qmd +++ b/numbers.qmd @@ -523,7 +523,7 @@ lead(x) You can lead or lag by more than one position by using the second argument, `n`. -### Consecutive identifies +### Consecutive identifiers Sometimes you want to start a new group every time some event occurs. For example, when you're looking at website data, it's common to want to break up events into sessions, where a session is defined as a gap of more than x minutes since the last activity. diff --git a/whole-game.qmd b/whole-game.qmd index 863da8e..b0e1a07 100644 --- a/whole-game.qmd +++ b/whole-game.qmd @@ -39,7 +39,7 @@ Five chapters focus on the tools of data science: - Before you can transform and visualize your data, you need to first get your data into R. In @sec-data-import you'll learn the basics of getting `.csv` files into R. -Nestled among these chapters that are five other chapters that focus on your R workflow. +Nestled among these chapters are five other chapters that focus on your R workflow. In @sec-workflow-basics, @sec-workflow-pipes, @sec-workflow-style, and @sec-workflow-scripts-projects you'll learn good workflow practices for writing and organizing your R code. These will set you up for success in the long run, as they'll give you the tools to stay organised when you tackle real projects. Finally, @sec-workflow-getting-help will teach you how to get help to keep learning.