who2

population

<p>A subset of data from the World Health Organization Global Tuberculosis
Report, and accompanying global populations. <code>who</code> uses the original
codes from the World Health Organization. The column names for columns
5 through 60 are made by combining <code>new_</code> with:</p><ul>
<li><p>the method of diagnosis (<code>rel</code> = relapse, <code>sn</code> = negative pulmonary
smear, <code>sp</code> = positive pulmonary smear, <code>ep</code> = extrapulmonary),</p></li>
<li><p>gender (<code>f</code> = female, <code>m</code> = male), and</p></li>
<li><p>age group (<code>014</code> = 0-14 yrs of age, <code>1524</code> = 15-24, <code>2534</code> = 25-34,
<code>3544</code> = 35-44 years of age, <code>4554</code> = 45-54, <code>5564</code> = 55-64,
<code>65</code> = 65 years or older).</p></li>
</ul><p></p><p></p><p><code>who2</code> is a lightly modified version that makes teaching the basics
easier by tweaking the variables to be slightly more consistent and
dropping <code>iso2</code> and <code>iso3</code>. <code>newrel</code> is replaced by <code>new_rel</code>, and a
<code>_</code> is added after the gender.</p>

datasets

Tools to help to create tidy data, where each column is a
variable, each row is an observation, and each cell contains a single
value.  'tidyr' contains tools for changing the shape (pivoting) and
hierarchy (nesting and 'unnesting') of a dataset, turning deeply
nested lists into rectangular data frames ('rectangling'), and
extracting values out of string columns. It also includes tools for
working with missing values (both implicit and explicit).

Hadley Wickham

tidyr

Tidy Messy Data

Davis Vaughan

Maximilian Girlich

Kevin Ushey

Posit Software, PBC 

who function


<div class="section" id="who">
<h3><code>who</code></h3><p></p><p>
</p><p>A data frame with 7,240 rows and 60 columns:</p><dl>
<dt>country</dt>
<dd><p>Country name</p></dd><p></p><p><dt>iso2, iso3</dt>
<dd><p>2 &amp; 3 letter ISO country codes</p></dd></p><p><dt>year</dt>
<dd><p>Year</p></dd></p><p><dt>new_sp_m014 - new_rel_f65</dt>
<dd><p>Counts of new TB cases recorded by group.
Column names encode three variables that describe the group.</p></dd></p><p>
</p></dl><p></p><p></p></div><p></p><p><div class="section" id="who-">
<h3><code>who2</code></h3></div></p><p>
</p><p>A data frame with 7,240 rows and 58 columns.</p>
<p></p><p><div class="section" id="population">
<h3><code>population</code></h3></div></p><p>
</p><p>A data frame with 4,060 rows and three columns:</p><dl>
<dt>country</dt>
<dd><p>Country name</p></dd><p></p><p><dt>year</dt>
<dd><p>Year</p></dd></p><p><dt>population</dt>
<dd><p>Population</p></dd></p><p>
</p></dl><p></p><p>
</p>

Format

<p>A subset of data from the World Health Organization Global Tuberculosis
Report, and accompanying global populations. <code>who</code> uses the original
codes from the World Health Organization. The column names for columns
5 through 60 are made by combining <code>new_</code> with:</p><ul>
<li><p>the method of diagnosis (<code>rel</code> = relapse, <code>sn</code> = negative pulmonary
smear, <code>sp</code> = positive pulmonary smear, <code>ep</code> = extrapulmonary),</p></li>
<li><p>gender (<code>f</code> = female, <code>m</code> = male), and</p></li>
<li><p>age group (<code>014</code> = 0-14 yrs of age, <code>1524</code> = 15-24, <code>2534</code> = 25-34,
<code>3544</code> = 35-44 years of age, <code>4554</code> = 45-54, <code>5564</code> = 55-64,
<code>65</code> = 65 years or older).</p></li>
</ul>

<p><code>who2</code> is a lightly modified version that makes teaching the basics
easier by tweaking the variables to be slightly more consistent and
dropping <code>iso2</code> and <code>iso3</code>. <code>newrel</code> is replaced by <code>new_rel</code>, and a
<code>_</code> is added after the gender.</p>

World Health Organization TB data — who


<div class='section' id='who'>
<h3><code>who</code></h3>


<p>A data frame with 7,240 rows and 60 columns:</p><dl>
<dt>country</dt>
<dd><p>Country name</p></dd>

<dt>iso2, iso3</dt>
<dd><p>2 &amp; 3 letter ISO country codes</p></dd>

<dt>year</dt>
<dd><p>Year</p></dd>

<dt>new_sp_m014 - new_rel_f65</dt>
<dd><p>Counts of new TB cases recorded by group.
Column names encode three variables that describe the group.</p></dd>


</dl>

</div>

<div class='section' id='who-'>
<h3><code>who2</code></h3>


<p>A data frame with 7,240 rows and 58 columns.</p>
</div>

<div class='section' id='population'>
<h3><code>population</code></h3>


<p>A data frame with 4,060 rows and three columns:</p><dl>
<dt>country</dt>
<dd><p>Country name</p></dd>

<dt>year</dt>
<dd><p>Year</p></dd>

<dt>population</dt>
<dd><p>Population</p></dd>


</dl>

</div>


who: World Health Organization TB data

Description

Usage

Arguments

Format

`who`

`who2`

`population`