Actually strip status

_common.R

@@ -39,10 +39,13 @@ status <- function(type) {
   )
 
   cat(paste0(
-    "::: status callout-", class, "\n",
+    "\n",
+    ":::: status\n",
+    "::: callout-", class, " \n",
     "You are reading the work-in-progress second edition of R for Data Science. ",
     "This chapter ", status, ". ",
     "You can find the complete first edition at <https://r4ds.had.co.nz>.\n",
-    ":::\n"
+    ":::\n",
+    "::::\n"
   ))
 }

oreilly/EDA.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-EDA">
-<h1><span id="sec-exploratory-data-analysis" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Exploratory data analysis</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-exploratory-data-analysis" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Exploratory data analysis</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/base-R.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-base-R">
-<h1><span id="sec-base-r" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">A field guide to base R</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p><p>To finish off the programming section, we’re going to give you a quick tour of the most important base R functions that we don’t otherwise discuss in the book. These tools are particularly useful as you do more programming and will help you read code that you’ll encounter in the wild.</p><p>This is a good place to remind you that the tidyverse is not the only way to solve data science problems. We teach the tidyverse in this book because tidyverse packages share a common design philosophy, which increases the consistency across functions, making each new function or package a little easier to learn and use. It’s not possible to use the tidyverse without using base R, so we’ve actually already taught you a <strong>lot</strong> of base R functions: from <code><a href="https://rdrr.io/r/base/library.html">library()</a></code> to load packages, to <code><a href="https://rdrr.io/r/base/sum.html">sum()</a></code> and <code><a href="https://rdrr.io/r/base/mean.html">mean()</a></code> for numeric summaries, to the factor, date, and POSIXct data types, and of course all the basic operators like <code>+</code>, <code>-</code>, <code>/</code>, <code>*</code>, <code>|</code>, <code>&amp;</code>, and <code>!</code>. What we haven’t focused on so far is base R workflows, so we will highlight a few of those in this chapter.</p><p>After you read this book you’ll learn other approaches to the same problems using base R, data.table, and other packages. You’ll certainly encounter these other approaches when you start reading R code written by other people, particularly if you’re using StackOverflow. It’s 100% okay to write code that uses a mix of approaches, and don’t let anyone tell you otherwise!</p><p>In this chapter, we’ll focus on four big topics: subsetting with <code>[</code>, subsetting with <code>[[</code> and <code>$</code>, the apply family of functions, and for loops. To finish off, we’ll briefly discuss two important plotting functions.</p>
+<h1><span id="sec-base-r" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">A field guide to base R</span></span></h1><p>To finish off the programming section, we’re going to give you a quick tour of the most important base R functions that we don’t otherwise discuss in the book. These tools are particularly useful as you do more programming and will help you read code that you’ll encounter in the wild.</p><p>This is a good place to remind you that the tidyverse is not the only way to solve data science problems. We teach the tidyverse in this book because tidyverse packages share a common design philosophy, which increases the consistency across functions, making each new function or package a little easier to learn and use. It’s not possible to use the tidyverse without using base R, so we’ve actually already taught you a <strong>lot</strong> of base R functions: from <code><a href="https://rdrr.io/r/base/library.html">library()</a></code> to load packages, to <code><a href="https://rdrr.io/r/base/sum.html">sum()</a></code> and <code><a href="https://rdrr.io/r/base/mean.html">mean()</a></code> for numeric summaries, to the factor, date, and POSIXct data types, and of course all the basic operators like <code>+</code>, <code>-</code>, <code>/</code>, <code>*</code>, <code>|</code>, <code>&amp;</code>, and <code>!</code>. What we haven’t focused on so far is base R workflows, so we will highlight a few of those in this chapter.</p><p>After you read this book you’ll learn other approaches to the same problems using base R, data.table, and other packages. You’ll certainly encounter these other approaches when you start reading R code written by other people, particularly if you’re using StackOverflow. It’s 100% okay to write code that uses a mix of approaches, and don’t let anyone tell you otherwise!</p><p>In this chapter, we’ll focus on four big topics: subsetting with <code>[</code>, subsetting with <code>[[</code> and <code>$</code>, the apply family of functions, and for loops. To finish off, we’ll briefly discuss two important plotting functions.</p>
 <section id="prerequisites" data-type="sect2">
 <h2>
 Prerequisites</h2>

oreilly/communicate-plots.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-communicate-plots">
-<h1><span id="sec-graphics-communication" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Graphics for communication</span></span></h1><p>::: status callout-important You are reading the work-in-progress second edition of R for Data Science. This chapter is currently a dumping ground for ideas, and we don’t recommend reading it. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-graphics-communication" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Graphics for communication</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/data-import.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-data-import">
-<h1><span id="sec-data-import" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Data import</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-data-import" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Data import</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>
@@ -373,7 +373,7 @@ Missing values, column types, and problems</h2>
 #&gt; # A tibble: 1 × 5
 #&gt;     row   col expected actual file                                    
 #&gt;   &lt;int&gt; &lt;int&gt; &lt;chr&gt;    &lt;chr&gt;  &lt;chr&gt;                                   
-#&gt; 1     3     1 a double .      /private/tmp/Rtmpc2nAIe/file8f2f488fc2f4</pre>
+#&gt; 1     3     1 a double .      /private/tmp/RtmpZYGhlj/file9e8176037b8c</pre>
 </div>
 <p>This tells us that there was a problem in row 3, col 1 where readr expected a double but got a <code>.</code>. That suggests this dataset uses <code>.</code> for missing values. So then we set <code>na = "."</code>, the automatic guessing succeeds, giving us the numeric column that we want:</p>
 <div class="cell">

oreilly/data-tidy.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-data-tidy">
-<h1><span id="sec-data-tidy" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Data tidying</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter is largely complete and just needs final proof reading. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-data-tidy" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Data tidying</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/data-transform.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-data-transform">
-<h1><span id="sec-data-transform" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Data transformation</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-data-transform" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Data transformation</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/databases.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-databases">
-<h1><span id="sec-import-databases" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Databases</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-import-databases" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Databases</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/datetimes.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-datetimes">
-<h1><span id="sec-dates-and-times" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Dates and times</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-dates-and-times" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Dates and times</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>
@@ -35,7 +35,7 @@ Creating date/times</h1>
 <pre data-type="programlisting" data-code-language="r">today()
 #&gt; [1] "2022-11-18"
 now()
-#&gt; [1] "2022-11-18 10:59:07 CST"</pre>
+#&gt; [1] "2022-11-18 11:36:09 CST"</pre>
 </div>
 <p>Otherwise, the following sections describe the four ways you’re likely to create a date/time:</p>
 <ul><li>While reading a file with readr.</li>

oreilly/factors.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-factors">
-<h1><span id="sec-factors" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Factors</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter is largely complete and just needs final proof reading. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-factors" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Factors</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/functions.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-functions">
-<h1><span id="sec-functions" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Functions</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-functions" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Functions</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/iteration.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-iteration">
-<h1><span id="sec-iteration" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Iteration</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-iteration" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Iteration</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/joins.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-joins">
-<h1><span id="sec-joins" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Joins</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-joins" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Joins</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/logicals.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-logicals">
-<h1><span id="sec-logicals" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Logical vectors</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-logicals" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Logical vectors</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/missing-values.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-missing-values">
-<h1><span id="sec-missing-values" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Missing values</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-missing-values" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Missing values</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/numbers.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-numbers">
-<h1><span id="sec-numbers" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Numbers</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-numbers" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Numbers</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/quarto-formats.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-quarto-formats">
-<h1><span id="sec-quarto-formats" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Quarto formats</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-quarto-formats" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Quarto formats</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/quarto-workflow.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-quarto-workflow">
-<h1><span id="sec-quarto-workflow" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Quarto workflow</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p><p>Earlier, we discussed a basic workflow for capturing your R code where you work interactively in the <em>console</em>, then capture what works in the <em>script editor</em>. Quarto brings together the console and the script editor, blurring the lines between interactive exploration and long-term code capture. You can rapidly iterate within a chunk, editing and re-executing with Cmd/Ctrl + Shift + Enter. When you’re happy, you move on and start a new chunk.</p><p>Quarto is also important because it so tightly integrates prose and code. This makes it a great <strong>analysis notebook</strong> because it lets you develop code and record your thoughts. An analysis notebook shares many of the same goals as a classic lab notebook in the physical sciences. It:</p><ul><li><p>Records what you did and why you did it. Regardless of how great your memory is, if you don’t record what you do, there will come a time when you have forgotten important details. Write them down so you don’t forget!</p></li>
+<h1><span id="sec-quarto-workflow" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Quarto workflow</span></span></h1><p>Earlier, we discussed a basic workflow for capturing your R code where you work interactively in the <em>console</em>, then capture what works in the <em>script editor</em>. Quarto brings together the console and the script editor, blurring the lines between interactive exploration and long-term code capture. You can rapidly iterate within a chunk, editing and re-executing with Cmd/Ctrl + Shift + Enter. When you’re happy, you move on and start a new chunk.</p><p>Quarto is also important because it so tightly integrates prose and code. This makes it a great <strong>analysis notebook</strong> because it lets you develop code and record your thoughts. An analysis notebook shares many of the same goals as a classic lab notebook in the physical sciences. It:</p><ul><li><p>Records what you did and why you did it. Regardless of how great your memory is, if you don’t record what you do, there will come a time when you have forgotten important details. Write them down so you don’t forget!</p></li>
 <li><p>Supports rigorous thinking. You are more likely to come up with a strong analysis if you record your thoughts as you go, and continue to reflect on them. This also saves you time when you eventually write up your analysis to share with others.</p></li>
 <li><p>Helps others understand your work. It is rare to do data analysis by yourself, and you’ll often be working as part of a team. A lab notebook helps you share not only what you’ve done, but why you did it with your colleagues or lab mates.</p></li>
 </ul><p>Much of the good advice about using lab notebooks effectively can also be translated to analysis notebooks. We’ve drawn on our own experiences and Colin Purrington’s advice on lab notebooks (<a href="https://colinpurrington.com/tips/lab-notebooks" class="uri">https://colinpurrington.com/tips/lab-notebooks</a>) to come up with the following tips:</p><ul><li><p>Ensure each notebook has a descriptive title, an evocative file name, and a first paragraph that briefly describes the aims of the analysis.</p></li>

oreilly/quarto.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-quarto">
-<h1><span id="sec-quarto" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Quarto</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-quarto" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Quarto</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/rectangling.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-rectangling">
-<h1><span id="sec-rectangling" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Data rectangling</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-rectangling" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Data rectangling</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/regexps.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-regexps">
-<h1><span id="sec-regular-expressions" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Regular expressions</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-regular-expressions" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Regular expressions</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/spreadsheets.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-spreadsheets">
-<h1><span id="sec-import-spreadsheets" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Spreadsheets</span></span></h1><p>::: status callout-important You are reading the work-in-progress second edition of R for Data Science. This chapter is currently a dumping ground for ideas, and we don’t recommend reading it. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-import-spreadsheets" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Spreadsheets</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/strings.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-strings">
-<h1><span id="sec-strings" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Strings</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p>
+<h1><span id="sec-strings" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Strings</span></span></h1>
 <section id="introduction" data-type="sect1">
 <h1>
 Introduction</h1>

oreilly/webscraping.html

@@ -1,2 +1,2 @@
 <section data-type="chapter" id="chp-webscraping">
-<h1><span id="sec-scraping" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Web scraping</span></span></h1><p>::: status callout-important You are reading the work-in-progress second edition of R for Data Science. This chapter is currently a dumping ground for ideas, and we don’t recommend reading it. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p></section>
+<h1><span id="sec-scraping" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Web scraping</span></span></h1></section>

oreilly/workflow-basics.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-workflow-basics">
-<h1><span id="sec-workflow-basics" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Workflow: basics</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p><p>You now have some experience running R code. We didn’t give you many details, but you’ve obviously figured out the basics, or you would’ve thrown this book away in frustration! Frustration is natural when you start programming in R, because it is such a stickler for punctuation, and even one character out of place will cause it to complain. But while you should expect to be a little frustrated, take comfort in that this experience is both typical and temporary: it happens to everyone, and the only way to get over it is to keep trying.</p><p>Before we go any further, let’s make sure you’ve got a solid foundation in running R code, and that you know about some of the most helpful RStudio features.</p>
+<h1><span id="sec-workflow-basics" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Workflow: basics</span></span></h1><p>You now have some experience running R code. We didn’t give you many details, but you’ve obviously figured out the basics, or you would’ve thrown this book away in frustration! Frustration is natural when you start programming in R, because it is such a stickler for punctuation, and even one character out of place will cause it to complain. But while you should expect to be a little frustrated, take comfort in that this experience is both typical and temporary: it happens to everyone, and the only way to get over it is to keep trying.</p><p>Before we go any further, let’s make sure you’ve got a solid foundation in running R code, and that you know about some of the most helpful RStudio features.</p>
 <section id="coding-basics" data-type="sect1">
 <h1>
 Coding basics</h1>

oreilly/workflow-help.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-workflow-help">
-<h1><span id="sec-workflow-getting-help" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Workflow: Getting help</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p><p>This book is not an island; there is no single resource that will allow you to master R. As you begin to apply the techniques described in this book to your own data, you will soon find questions that we do not answer. This section describes a few tips on how to get help, and to help you keep learning.</p>
+<h1><span id="sec-workflow-getting-help" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Workflow: Getting help</span></span></h1><p>This book is not an island; there is no single resource that will allow you to master R. As you begin to apply the techniques described in this book to your own data, you will soon find questions that we do not answer. This section describes a few tips on how to get help, and to help you keep learning.</p>
 <section id="google-is-your-friend" data-type="sect1">
 <h1>
 Google is your friend</h1>

oreilly/workflow-pipes.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-workflow-pipes">
-<h1><span id="sec-workflow-pipes" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Workflow: Pipes</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter is largely complete and just needs final proof reading. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p><p>The pipe, <code>|&gt;</code>, is a powerful tool for clearly expressing a sequence of operations that transform an object. We briefly introduced pipes in the previous chapter, but before going too much farther, we want to give a few more details and discuss <code>%&gt;%</code>, a predecessor to <code>|&gt;</code>.</p><p>To add the pipe to your code, we recommend using the build-in keyboard shortcut Ctrl/Cmd + Shift + M. You’ll need to make one change to your RStudio options to use <code>|&gt;</code> instead of <code>%&gt;%</code> as shown in <a href="#fig-pipe-options" data-type="xref">#fig-pipe-options</a>; more on <code>%&gt;%</code> shortly.</p><div class="cell">
+<h1><span id="sec-workflow-pipes" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Workflow: Pipes</span></span></h1><p>The pipe, <code>|&gt;</code>, is a powerful tool for clearly expressing a sequence of operations that transform an object. We briefly introduced pipes in the previous chapter, but before going too much farther, we want to give a few more details and discuss <code>%&gt;%</code>, a predecessor to <code>|&gt;</code>.</p><p>To add the pipe to your code, we recommend using the build-in keyboard shortcut Ctrl/Cmd + Shift + M. You’ll need to make one change to your RStudio options to use <code>|&gt;</code> instead of <code>%&gt;%</code> as shown in <a href="#fig-pipe-options" data-type="xref">#fig-pipe-options</a>; more on <code>%&gt;%</code> shortly.</p><div class="cell">
 <div class="cell-output-display">
 
 <figure id="fig-pipe-options"><p><img src="screenshots/rstudio-pipe-options.png" alt="Screenshot showing the &quot;Use native pipe operator&quot; option which can be found on the &quot;Editing&quot; panel of the &quot;Code&quot; options." width="616"/></p>

oreilly/workflow-scripts.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-workflow-scripts">
-<h1><span id="sec-workflow-scripts-projects" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Workflow: scripts and projects</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p><p>This chapter will introduce you to two very important tools for organizing your code: scripts and projects.</p>
+<h1><span id="sec-workflow-scripts-projects" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Workflow: scripts and projects</span></span></h1><p>This chapter will introduce you to two very important tools for organizing your code: scripts and projects.</p>
 <section id="scripts" data-type="sect1">
 <h1>
 Scripts</h1>

oreilly/workflow-style.html

@@ -1,5 +1,5 @@
 <section data-type="chapter" id="chp-workflow-style">
-<h1><span id="sec-workflow-style" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Workflow: code style</span></span></h1><p>::: status callout-note You are reading the work-in-progress second edition of R for Data Science. This chapter should be readable but is currently undergoing final polishing. You can find the complete first edition at <a href="https://r4ds.had.co.nz" class="uri">https://r4ds.had.co.nz</a>. :::</p><p>Good coding style is like correct punctuation: you can manage without it, butitsuremakesthingseasiertoread. Even as a very new programmer it’s a good idea to work on your code style. Using a consistent style makes it easier for others (including future-you!) to read your work, and is particularly important if you need to get help from someone else. This chapter will introduce to the most important points of the <a href="https://style.tidyverse.org">tidyverse style guide</a>, which is used throughout this book.</p><p>Styling your code will feel a bit tedious to start with, but if you practice it, it will soon become second nature. Additionally, there are some great tools to quickly restyle existing code, like the <a href="https://styler.r-lib.org">styler</a> package by Lorenz Walthert. Once you’ve installed it with <code>install.packages("styler")</code>, an easy way to use it is via RStudio’s <strong>command palette</strong>. The command palette lets you use any build-in RStudio command, as well as many addins provided by packages. Open the palette by pressing Cmd/Ctrl + Shift + P, then type “styler” to see all the shortcuts provided by styler. <a href="#fig-styler" data-type="xref">#fig-styler</a> shows the results.</p><div class="cell">
+<h1><span id="sec-workflow-style" class="quarto-section-identifier d-none d-lg-block"><span class="chapter-title">Workflow: code style</span></span></h1><p>Good coding style is like correct punctuation: you can manage without it, butitsuremakesthingseasiertoread. Even as a very new programmer it’s a good idea to work on your code style. Using a consistent style makes it easier for others (including future-you!) to read your work, and is particularly important if you need to get help from someone else. This chapter will introduce to the most important points of the <a href="https://style.tidyverse.org">tidyverse style guide</a>, which is used throughout this book.</p><p>Styling your code will feel a bit tedious to start with, but if you practice it, it will soon become second nature. Additionally, there are some great tools to quickly restyle existing code, like the <a href="https://styler.r-lib.org">styler</a> package by Lorenz Walthert. Once you’ve installed it with <code>install.packages("styler")</code>, an easy way to use it is via RStudio’s <strong>command palette</strong>. The command palette lets you use any build-in RStudio command, as well as many addins provided by packages. Open the palette by pressing Cmd/Ctrl + Shift + P, then type “styler” to see all the shortcuts provided by styler. <a href="#fig-styler" data-type="xref">#fig-styler</a> shows the results.</p><div class="cell">
 <div class="cell-output-display">
 
 <figure id="fig-styler"><p><img src="screenshots/rstudio-palette.png" alt="A screenshot showing the command palette after typing &quot;styler&quot;, showing the four styling tool provided by the package." width="638"/></p>