<p><div><div><div><div data-show-faces="false" data-height="21" data-width="100" data-layout="button_count" data-send="true" data-href="https://www.r-bloggers.com/digital-marketplace-six-months-later/"></div></div><div></div></div><div></div></div>
<div>
(This article was first published on <strong><a href="https://thinkr.biz/2018/04/02/digital-marketplace-six-months-later/"> R – thinkr</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<h2>Revisiting an old post</h2>
<p>Last September I wrote a post entitled <a rel="nofollow" href="https://thinkr.biz/2017/09/12/government-ambition-smes/" target="_blank">Is the Government realising its ambition for SMEs on G-Cloud?</a> Six months on, I wanted to revisit and update this article, fold in a second Digital Marketplace framework, and share the <a rel="nofollow" href="https://thinkr.biz/wp-content/uploads/2018/04/DM.html" target="_blank">R code here</a>. Revisiting an old post also provides an opportunity to see if one can simplify and improve older code.<span></span></p>
<p>Every 7.8 months, on average, suppliers are asked to resubmit their G-Cloud offerings with the lastest pricing and service descriptions. It’s a chance for new suppliers, often smaller ones, to join the existing list and increase overall competitiveness for Cloud services.</p>
<p><a rel="nofollow" href="http://central-government.governmentcomputing.com/news/g-cloud-10-set-for-june-2018-go-live-date-6074061" target="_blank">G-Cloud 10 is expected to go live in June</a>.</p>
<p><img sizes="(max-width: 767px) 89vw, (max-width: 1000px) 54vw, (max-width: 1071px) 543px, 580px" src="https://i2.wp.com/thinkr.biz/wp-content/uploads/2018/04/Versions-1.png?w=450&ssl=1" alt="" class="wp-image-744" data-recalc-dims="1"></p>
<p>Last September’s article showed signs of a weakening in the Small &amp; Medium Enterprise (SME) supplier share of G-Cloud sales by value. This plot shows this trend to have persisted, and reflects the Digital Outcomes &amp; Specialists (DOS) framework also exhibiting a downward trend.</p>
<p><img sizes="(max-width: 767px) 89vw, (max-width: 1000px) 54vw, (max-width: 1071px) 543px, 580px" src="https://i1.wp.com/thinkr.biz/wp-content/uploads/2018/04/Frameworks-1.png?w=450&ssl=1" alt="" class="wp-image-741" data-recalc-dims="1"></p>
<p>Overall spending through the two frameworks however continues to grow across all parts of Public Sector.</p>
<p><img sizes="(max-width: 767px) 89vw, (max-width: 1000px) 54vw, (max-width: 1071px) 543px, 580px" src="https://i0.wp.com/thinkr.biz/wp-content/uploads/2018/04/Sectors-1.png?w=450&ssl=1" alt="" class="wp-image-742" data-recalc-dims="1"></p>
<p>With the weakening in SME share reflected in most sectors.</p>
<p><img sizes="(max-width: 767px) 89vw, (max-width: 1000px) 54vw, (max-width: 1071px) 543px, 580px" src="https://i1.wp.com/thinkr.biz/wp-content/uploads/2018/04/SME-1.png?w=450&ssl=1" alt="" class="wp-image-743" data-recalc-dims="1"></p>
<h2>R toolkit</h2>
<p>Revisiting older code prompted me to try automating the routinely, albeit to date manually, produced R toolkit summary. See the <a rel="nofollow" href="https://thinkr.biz/wp-content/uploads/2018/04/DM.html" target="_blank">code for the automated version</a>. This also now incorporates a count of function usage, arranged with the most-used listed first for each package.</p>
<p>I’m excluding the <code>base</code> and <code>stats</code> packages. I’m doing that because, for example, <code>dplyr::filter()</code> masks <code>stats::filter()</code>, and the toolkit summary would imply I’ve used both when my first instinct is “all things tidyverse”. And I’m anyway more interested in my usage of “non-base” functions.</p>
<div>
<table>
<thead>
<tr>
<th> </th>
<th><strong>Packages</strong></th>
<th><strong>Functions</strong></th>
</tr>
</thead>
<tbody>
<tr>
<td><img src="https://i1.wp.com/thinkr.biz/wp-content/uploads/2017/10/Program-e1509478672361.png?resize=100%2C100&ssl=1" alt="" width="100" class="wp-image-135" data-recalc-dims="1" height="100"></td>
<td>purrr</td>
<td>map[1]; map2_df[1]; possibly[1]; set_names[1]</td>
</tr>
<tr>
<td><img src="https://i0.wp.com/thinkr.biz/wp-content/uploads/2017/10/Import-e1509478685299.png?resize=100%2C100&ssl=1" alt="" width="100" class="wp-image-134" data-recalc-dims="1" height="100"></td>
<td>readr</td>
<td>guess_encoding[2]; locale[2]; read_csv[2]; parse_number[1]</td>
</tr>
<tr>
<td rowspan="6"><img src="https://i2.wp.com/thinkr.biz/wp-content/uploads/2017/10/Transform-e1509478657749.png?resize=100%2C100&ssl=1" alt="" width="100" class="wp-image-136" data-recalc-dims="1" height="100"></td>
<td>dplyr</td>
<td>filter[8]; group_by[5]; mutate[5]; select[5]; summarize[5]; arrange[1]; as_tibble[1]; bind_rows[1]; data_frame[1]; desc[1]; if_else[1]</td>
</tr>
<tr>
<td>tibble</td>
<td>as_tibble[1]; data_frame[1]; enframe[1]</td>
</tr>
<tr>
<td>stringr</td>
<td>fixed[7]; str_c[4]; str_replace[4]; str_remove[3]; str_count[1]; str_detect[1]; str_extract[1]</td>
</tr>
<tr>
<td>rebus</td>
<td>literal[1]</td>
</tr>
<tr>
<td>lubridate</td>
<td>myd[2]; days_in_month[1]; month[1]</td>
</tr>
<tr>
<td>tidyr</td>
<td>unnest[1]</td>
</tr>
<tr>
<td rowspan="5"><img src="https://i1.wp.com/thinkr.biz/wp-content/uploads/2017/10/Visualize-e1509478640644.png?resize=100%2C100&ssl=1" alt="" width="100" class="wp-image-137" data-recalc-dims="1" height="100"></td>
<td>ggplot2</td>
<td>labs[5]; aes[4]; geom_line[4]; geom_smooth[4]; ggplot[4]; ggtitle[4]; scale_x_date[4]; theme[3]; element_rect[2]; facet_wrap[2]; scale_y_continuous[1]</td>
</tr>
<tr>
<td>scales</td>
<td>percent_format[1]</td>
</tr>
<tr>
<td>ggthemes</td>
<td>scale_colour_economist[4]; theme_economist[1]</td>
</tr>
<tr>
<td>kableExtra</td>
<td>kable[1]; kable_styling[1]</td>
</tr>
<tr>
<td>knitr</td>
<td>kable[1]</td>
</tr>
</tbody>
</table>
</div>
<p></p>
<p>View the code <a rel="nofollow" href="https://thinkr.biz/wp-content/uploads/2018/04/DM.html" target="_blank">here</a>.</p>
<h3>Citations</h3>
<p>R Development Core Team (2008). R: A language and environment for<br>
statistical computing. R Foundation for Statistical Computing,<br>
Vienna, Austria. ISBN 3-900051-07-0, URL <a rel="nofollow" href="http://www.r-project.org/" target="_blank">http://www.R-project.org</a>.</p>
<p>Contains public sector information licensed under the <a rel="nofollow" href="https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/" target="_blank">Open Government Licence v3.0</a>.</p>
<p>The post <a rel="nofollow" href="https://thinkr.biz/2018/04/02/digital-marketplace-six-months-later/" target="_blank">Digital Marketplace. Six months later.</a> appeared first on <a rel="nofollow" href="https://thinkr.biz/" target="_blank">thinkr</a>.</p>
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