v1.0.0

Author: gagolews

CITATION.cff

@@ -1,17 +1,18 @@
 cff-version: 1.2.0
-message: "Please cite this book as below."
+message: "Please cite this book as follows."
 title: "Deep R Programming"
 doi: 10.5281/zenodo.7490464
 url: "https://deepr.gagolewski.com/"
 repository-code: "https://github.com/gagolews/deepr"
 abstract: >
-    Deep R Programming is a comprehensive course on one of the most popular
-    languages in data science (statistical computing, graphics, machine
-    learning, data wrangling and analytics). It introduces the base language
-    in-depth. It is aimed at ambitious students, professionals, and researchers
-    who would like to become independent users of this powerful environment.
-    This textbook is a non-profit project. Its online and PDF versions
-    are freely available at https://deepr.gagolewski.com/.
+    Deep R Programming is a comprehensive and in-depth introductory course on
+    one of the most popular languages for data science. It equips ambitious
+    students, professionals, and researchers with the knowledge and skills to
+    become independent users of this potent environment so that they can tackle
+    any problem related to data wrangling and analytics, numerical computing,
+    statistics, and machine learning. This textbook is a non-profit project.
+    Its online and PDF versions are freely available at
+    https://deepr.gagolewski.com/.
 keywords:
   - R
   - S

README.md

@@ -1,6 +1,6 @@
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docs/_images/animation-1.png

@@ -10,12 +10,12 @@
 <meta content="https://deepr.gagolewski.com/deepr.pdf" name="citation_pdf_url" />
 <meta content="https://deepr.gagolewski.com" name="citation_public_url" />
 <meta content="10.5281/zenodo.7490464" name="citation_doi" />
-<meta content="Deep R Programming is comprehensive course on one of the most popular languages for data science (statistical computing, graphics, machine learning, data wrangling and analytics). It introduces the base language in-depth. It is aimed at ambitious students, professionals, and researchers who would like to become independent users of this powerful environment. This textbook is a non-profit project. Its online and PDF versions are freely available at https://deepr.gagolewski.com/." name="citation_abstract" />
+<meta content="Deep R Programming is a comprehensive and in-depth introductory course on one of the most popular languages for data science. It equips ambitious students, professionals, and researchers with the knowledge and skills to become independent users of this potent environment so that they can tackle any problem related to data wrangling and analytics, numerical computing, statistics, and machine learning. This textbook is a non-profit project. Its online and PDF versions are freely available at https://deepr.gagolewski.com/." name="citation_abstract" />
 <meta content="summary" name="twitter:card" />
 <meta content="Deep R Programming" name="twitter:title" />
 <meta content="Deep R Programming" name="og:title" />
-<meta content="Deep R Programming is comprehensive course on one of the most popular languages for data science (statistical computing, graphics, machine learning, data wrangling and analytics). It introduces the base language in-depth. It is aimed at ambitious students, professionals, and researchers who would like to become independent users of this powerful environment. This textbook is a non-profit project. Its online and PDF versions are freely available at https://deepr.gagolewski.com/." name="twitter:description" />
-<meta content="Deep R Programming is comprehensive course on one of the most popular languages for data science (statistical computing, graphics, machine learning, data wrangling and analytics). It introduces the base language in-depth. It is aimed at ambitious students, professionals, and researchers who would like to become independent users of this powerful environment. This textbook is a non-profit project. Its online and PDF versions are freely available at https://deepr.gagolewski.com/." name="og:description" />
+<meta content="Deep R Programming is a comprehensive and in-depth introductory course on one of the most popular languages for data science. It equips ambitious students, professionals, and researchers with the knowledge and skills to become independent users of this potent environment so that they can tackle any problem related to data wrangling and analytics, numerical computing, statistics, and machine learning. This textbook is a non-profit project. Its online and PDF versions are freely available at https://deepr.gagolewski.com/." name="twitter:description" />
+<meta content="Deep R Programming is a comprehensive and in-depth introductory course on one of the most popular languages for data science. It equips ambitious students, professionals, and researchers with the knowledge and skills to become independent users of this potent environment so that they can tackle any problem related to data wrangling and analytics, numerical computing, statistics, and machine learning. This textbook is a non-profit project. Its online and PDF versions are freely available at https://deepr.gagolewski.com/." name="og:description" />
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@@ -190,7 +190,7 @@
 <div class="sidebar-brand">
 An open-access textbook<br />
 by <a href='https://www.gagolewski.com' style="display: contents">Marek Gagolewski</a><br />
-v0.9.9.9009 (draft)
+v1.0.0
 </div>
 <form class="sidebar-search-container" method="get" action="../search.html" role="search">
   <input class="sidebar-search" placeholder="Search" name="q" aria-label="Search">
@@ -231,10 +231,10 @@
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Deepest</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="310-compiled.html">14. Interfacing compiled code (**)</a></li>
-<li class="toctree-l1"><a class="reference internal" href="320-language.html">15. Unevaluated expressions (*)</a></li>
-<li class="toctree-l1"><a class="reference internal" href="330-environment.html">16. Environments and evaluation (*)</a></li>
-<li class="toctree-l1"><a class="reference internal" href="340-lazy.html">17. Lazy evaluation (**)</a></li>
+<li class="toctree-l1"><a class="reference internal" href="310-compiled.html">14. Interfacing compiled code (**)</a></li>
+<li class="toctree-l1"><a class="reference internal" href="320-language.html">15. Unevaluated expressions (*)</a></li>
+<li class="toctree-l1"><a class="reference internal" href="330-environment.html">16. Environments and evaluation (*)</a></li>
+<li class="toctree-l1"><a class="reference internal" href="340-lazy.html">17. Lazy evaluation (**)</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Appendix</span></p>
 <ul>
@@ -437,22 +437,22 @@ <h2>To R, or not to R<a class="headerlink" href="#to-r-or-not-to-r" title="Perma
 will be much easier later. After all, R is not the only
 notable environment out there.</p>
 <p>Anyway, enough preaching. This graduate<a class="footnote-reference brackets" href="#footwut" id="id11" role="doc-noteref"><span class="fn-bracket">[</span>4<span class="fn-bracket">]</span></a>-level textbook is for
-independent readers who:</p>
+readers who:</p>
 <ul class="simple">
-<li><p>do not mind a slightly steeper learning curve
-at the beginning,</p></li>
+<li><p>would like to experience the <em>joy</em> of solving problems by programming,</p></li>
+<li><p>want to become <em>independent</em> users of the R environment,</p></li>
 <li><p>can appreciate a more cohesively and
 comprehensively<a class="footnote-reference brackets" href="#footidealise" id="id12" role="doc-noteref"><span class="fn-bracket">[</span>5<span class="fn-bracket">]</span></a> organised material,</p></li>
-<li><p>would like to experience the joy of solving problems by programming,</p></li>
+<li><p>do not mind a slightly steeper learning curve at the beginning,</p></li>
 <li><p>do not want to be made obsolete by artificial “intelligence”
 in the future.</p></li>
 </ul>
-<p>Some will benefit from it as a first introduction to R (yet,
+<p>Some readers will benefit from its being their first introduction to R (yet,
 without all the pampering). For others<a class="footnote-reference brackets" href="#footothers" id="id13" role="doc-noteref"><span class="fn-bracket">[</span>6<span class="fn-bracket">]</span></a>, this will be a fine
 course from intermediate to advanced (do not skip the first
 chapters, though).</p>
-<p>Either way, do not forget to solve <em>all</em> the prescribed exercises.</p>
-<p>Good luck.</p>
+<p>Either way, we should not forget to solve <em>all</em> the prescribed exercises.</p>
+<p>Good luck!</p>
 </section>
 <section id="classification-of-r-data-types-and-book-structure">
 <h2>Classification of R data types and book structure<a class="headerlink" href="#classification-of-r-data-types-and-book-structure" title="Permalink to this heading">#</a></h2>
@@ -523,7 +523,7 @@ <h2>Classification of R data types and book structure<a class="headerlink" href=
 as well as introduce the basic ways to prepare
 publication-quality graphics (<a class="reference internal" href="250-graphics.html#chap-graphics"><span class="std std-numref">Chapter 13</span></a>).</p>
 </li>
-<li><p>Some more advanced material is discussed in the third part.
+<li><p>More advanced material is discussed in the third part.
 For most readers, it should be of theoretical interest only.
 However, it can help gain a complete understanding
 of and control over our environment.
@@ -568,7 +568,7 @@ <h2>Classification of R data types and book structure<a class="headerlink" href=
 <em>IEEE Transactions on Fuzzy Systems</em>, and <em>Journal of Informetrics</em>.</p>
 <p>In my “spare” time, I write books for my students: check out my
 <a class="reference external" href="https://datawranglingpy.gagolewski.com/"><em>Minimalist Data Wrangling with Python</em></a> <span id="id15">[<a class="reference internal" href="999-bibliography.html#id3" title="Gagolewski, M. (2022).  Minimalist Data Wrangling with Python. Zenodo. URL: https://datawranglingpy.gagolewski.com/, DOI: 10.5281/zenodo.6451068.">26</a>]</span>.
-I also develop open-source (libre) data analysis software,
+I also develop open-source data analysis software,
 such as <a class="reference external" href="https://stringi.gagolewski.com/"><strong class="program">stringi</strong></a>
 (one of the most often downloaded R packages),
 <a class="reference external" href="https://genieclust.gagolewski.com/"><strong class="program">genieclust</strong></a>
@@ -650,7 +650,7 @@ <h2>You can make this book better<a class="headerlink" href="#you-can-make-this-
 </aside>
 <aside class="footnote brackets" id="footr049" role="note">
 <span class="label"><span class="fn-bracket">[</span><a role="doc-backlink" href="#id7">2</a><span class="fn-bracket">]</span></span>
-<p>See <span id="id18">[<a class="reference internal" href="999-bibliography.html#id20" title="Chambers, J.M. (2020).  S, R, and data science. The R Journal, 12(1):462–476. DOI: 10.32614/RJ-2020-028.">12</a>, <a class="reference internal" href="999-bibliography.html#id18" title="Ihaka, R. and Gentleman, R. (1996).  R: A language for data analysis and graphics. Journal of Computational and Graphical Statistics, 5(3):299–314. URL: https://www.stat.auckland.ac.nz/~ihaka/downloads/R-paper.pdf, DOI: 10.1080/10618600.1996.10474713.">37</a>]</span> for some historical
+<p>See <span id="id18">[<a class="reference internal" href="999-bibliography.html#id20" title="Chambers, J.M. (2020).  S, R, and data science. The R Journal, 12(1):462–476. DOI: 10.32614/RJ-2020-028.">12</a>, <a class="reference internal" href="999-bibliography.html#id18" title="Ihaka, R. and Gentleman, R. (1996).  R: A language for data analysis and graphics. Journal of Computational and Graphical Statistics, 5(3):299–314. URL: https://www.stat.auckland.ac.nz/~ihaka/downloads/R-paper.pdf, DOI: 10.1080/10618600.1996.10474713.">37</a>]</span> for historical
 notes. R version 0.49 released in April 1997 (the first whose
 source code is available on CRAN;
 see <a class="reference external" href="https://cloud.r-project.org/src/base/R-0">https://cloud.r-project.org/src/base/R-0</a>),
@@ -669,11 +669,9 @@ <h2>You can make this book better<a class="headerlink" href="#you-can-make-this-
 <aside class="footnote brackets" id="footwut" role="note">
 <span class="label"><span class="fn-bracket">[</span><a role="doc-backlink" href="#id11">4</a><span class="fn-bracket">]</span></span>
 <p>The author taught similar courses for his wonderfully
-ambitious undergraduate data/computer science and maths students at
-Warsaw University of Technology, where such an approach
-has proven not difficult at all. It requires a more independent,
-curious, and motivated mindset, though.
-And that’s the way to go in the long run.</p>
+ambitious undergraduate data/computer science and mathematics students
+at the Warsaw University of Technology, where our approach
+has proven not difficult whatsoever.</p>
 </aside>
 <aside class="footnote brackets" id="footidealise" role="note">
 <span class="label"><span class="fn-bracket">[</span><a role="doc-backlink" href="#id12">5</a><span class="fn-bracket">]</span></span>
@@ -686,7 +684,7 @@ <h2>You can make this book better<a class="headerlink" href="#you-can-make-this-
 </aside>
 <aside class="footnote brackets" id="footothers" role="note">
 <span class="label"><span class="fn-bracket">[</span><a role="doc-backlink" href="#id13">6</a><span class="fn-bracket">]</span></span>
-<p>It might also happen that for some, this will not
+<p>It might also happen that for certain readers, this will not
 be an appropriate course at all, either at this stage of their career
 (come back later) or in general (no dramas).
 This is a non-profit, open-access project, but it does not
@@ -739,7 +737,7 @@ <h2>You can make this book better<a class="headerlink" href="#you-can-make-this-
               Some rights reserved. Licensed under <a href='https://creativecommons.org/licenses/by-nc-nd/4.0/'>CC BY-NC-ND 4.0</a>.
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-              Last updated on 2023-06-27T15:21:15+1000.
+              Last updated on 2023-06-28T16:02:43+1000.
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