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<a href="https://kevinwang09.github.io/tidytuesday/2020.html">2020</a>
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<a href="https://kevinwang09.github.io/tidytuesday/2019.html">2019</a>
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</div>
<h1 class="title toc-ignore">Kevin’s TidyTuesdays in 2019</h1>
</div>
<div id="introduction" class="section level1">
<h1>Introduction</h1>
<p>This webpage was originally designed to host all of my work for the
<a href="https://github.com/rfordatascience/tidytuesday">tidytuesday</a>
challenge.</p>
<p>However, as a data scientist, I often need a quick workspace to host
all my other statistical analytics. Hence, as my analytical interests
are not limited to just tidytuesday datasets, I also use this repo to
host a whole range RMarkdown HTML reports.</p>
<p>This webpage was deployed through GitHub Actions and GitHub
Pages.</p>
</div>
<div id="jan-03---bushfire" class="section level1">
<h1>2020 Jan 03 - bushfire</h1>
<p>This is not a fun exercise. I live in Australia and Australia is now
hit with unprecedented number of bushfires. My house is about 30 mins
drive from the nearest bushfire this week. I grabbed the NASA - FIRMS
data and made a visualisation of the spread of bushfire around my house
in the past 30 days.</p>
<p>See <a href="bushfire/NASA_FIRMS.html">here</a> for the RMarkdown
generated HTML document.</p>
<p><img src="bushfire/Nowra_fire.gif" width="400" height="300" /></p>
</div>
<div id="dec-07---side-by-side-plots" class="section level1">
<h1>2019 Dec 07 - Side-by-side plots</h1>
<p><a href="side-plots/side-plots.html">This</a> is a very small (blog)
post about making side-by-side plots, in celebration of
<code>patchwork</code> being uploaded onto CRAN. A more complex example
using clustering can be found <a
href="side-plots/dim_redu.html">here</a>.</p>
</div>
<div id="nov-28---uac-atar-scaling" class="section level1">
<h1>2019 Nov 28 - UAC ATAR scaling</h1>
<p>This is my own personal project. The idea is to scrape the HSC
scaling data from UAC published PDF. See the script for download <a
href="hsc/download_UAC.R">here</a>, analysis will be made available
later. Some intermediate work are <a
href="hsc/get_all_docs.Rmd">here</a></p>
</div>
<div id="nov-04---cricket" class="section level1">
<h1>2019 Nov 04 - Cricket</h1>
<p>This is my own personal project. A small website is <a
href="cricket/index.html">here</a>.</p>
<p>If you are interested in all the analytics that I have done in
cricket analytics, see <a
href="https://github.com/kevinwang09/cricinformatics">Cricinformatics</a>.</p>
<p>I will merge this analysis with Cricinformatics soon.</p>
</div>
<div id="aug-13---roman-emperors" class="section level1">
<h1>2019 Aug 13 - Roman Emperors</h1>
<p>RMarkdown generated HTML document is <a
href="2019-08-13-emperors/emperors.html">here</a>.</p>
<p>Summary of findings:</p>
<ul>
<li>This analysis is incomplete and should be resumed at a future
date.</li>
<li>Being an emperor is a highly risky job. You are more likely to die
from assassination than any other causes.</li>
<li>A good advice on having a long reign is to make your rise to power
be somewhat peaceful. That means you better be someone who can inherit
the empire through birthright.</li>
</ul>
<p><img src="2019-08-13-emperors/boxplot_reign.png" width="600" height="400" /></p>
<ul>
<li><p>The previous analysis gave me an idea to set up a framework to do
a survival analysis of the time which emperors reign.</p>
<ol style="list-style-type: decimal">
<li>Consider only the emperors that died during their reign with known
causes.</li>
<li>The time which an emperor reigns is the observed survival time.</li>
<li>If an emperor dies of natural causes, then I will interpret that to
mean this emperor has truly reached the end of his life. So in the
language of survival analysis, I will label this emperor as truly
“dead”.</li>
<li>If an emperor dies of other causes, then I will interpret that to
mean this emperor has his life cut-short. So in the language of survival
analysis, I will label this emperor as “censored”.</li>
<li>Of course, this analysis is problematic because each observation is
not independent. I mean, these emperors love killing each other! But
this is a very simple attempt to incorporate the problem of unnatural
death into an analysis of the reign of emperors based on their original
rise to power.</li>
</ol></li>
</ul>
<p><img src="2019-08-13-emperors/surv_plot_emperor_rise.png" width="400" height="300" /></p>
<ul>
<li><p>Below: timeline plot combining cause of death and rise of
power.</p>
<ul>
<li>Around 150 AD, there is a series of emperors that are rose to
powerful peacefully and also died of natural causes. Interestingly,
towards the end of the available data, there is also a group of emperors
that rose to power peacefully but had a mixture of causes of death.</li>
<li>Around 250 AD, there is a series of emperors that rose to power by
also killed.</li>
</ul>
<p>Both of these time-dependent trends were not shown in the “survival
analysis” above. This is why I criticise the survival analysis above
since these time effects are taken into account for the reigning time of
the emperors. Namly, during turbulent periods of the history, emperors
are more likely to die regardless of their rise to power.</p></li>
</ul>
<p><img src="2019-08-13-emperors/timeline_plot.png" width="600" height="400" /></p>
</div>
<div id="jul-23---birds-impact" class="section level1">
<h1>2019 Jul 23 - Birds impact</h1>
<p>Report can be found <a
href="2019-07-23-bird_impacts/bird_impacts.html">here</a>.</p>
<p>Summary of findings:</p>
<ul>
<li>This analysis is incomplete and should be resumed at a future date.
I find this data to be much messier than previous weeks, and this gets
me excited. Messy data is like a puzzle and I like puzzles.</li>
<li>This is a data on number of bird impact incidents with airplanes in
the US between 1990 and 2018. Unfortunately, due to limited
supplementary data available, the analysis I can do at this stage is
limited.</li>
<li>As expected, we find that the birds impact incidents are seasonal
with less incidents during the winter months. However, we cannot
conclude whether this is due to inactivities of birds during these
months or due to reduced number of flights.</li>
</ul>
<p><img src="2019-07-23-bird_impacts/incidents_2018.gif" width="600" height="400" /></p>
<ul>
<li>Another interesting trend is that there is a dip in the number of
incidents around June every year. And this dip was only visible for
flights around night times. This could be due to the scheduling of the
flights around this time of the year.</li>
</ul>
<p><img src="2019-07-23-bird_impacts/combine_trace_plot.png" width="800" height="600" /></p>
<p><strong>Key things that I learnt</strong>:</p>
<ul>
<li>I am getting a bit better at using the <code>gganimate</code>
package. This time, it integrated very smoothly with the
<code>maps</code> package.</li>
<li>One observation on the performance of <code>gganimate</code>: it is
usually very fast for simple plots (say 24 fps), but it can be 10 times
slower for more complicated plots (2 ~ 3 fps for the map above).</li>
</ul>
</div>
<div id="may-28---wines-around-the-world" class="section level1">
<h1>2019 May 28 - Wines around the world</h1>
<p>Report can be found <a href="2019-05-28-wine/wine.html">here</a></p>
<p>Summary: I chose not to publish a thorough detailed analysis because
I have used this dataset for teaching purposes at my institution.</p>
</div>
<div id="may-21---plastic-waste" class="section level1">
<h1>2019 May 21 - Plastic waste</h1>
<p>Report can be found <a
href="2019_05_21-plastic/2019_05_21.html">here</a></p>
<p>Summary: It is known that there is a positive correlation between GDP
of a country and the amount of plastic waste produced by a country. One
reason for this is that wealthier nations demands more goods/resources
and therefore produces more waste during consumptions. There are many
wonderful visualisations of this trend already on Twitter.</p>
<p>I am personally interested in another metric: GDP growth. My
reasoning is that when a country has a high GDP growth, the expansion in
economic activities (e.g. industrial production) will yield more waste.
This is a hard hypothesis to verify due that the waste data is only
available for the year of 2010 and the messy World Bank data.</p>
<p><strong>Key things that I learnt</strong>:</p>
<ul>
<li><code>gganimate</code> package went through significant updates
since I used it in 2016. The package’s functionalities have been
enhanced, particularly in respect to the speed/aesthetics of the
transitions.</li>
<li>Additionally, the <code>ggpubr</code> package provides some
important functions that allows rapid annotations on ggplot figures (in
this case, correlation value).</li>
</ul>
<p><img src="2019_05_21-plastic/gdp_growth_vs_plastic_per_cap.gif" width="600" height="400" /></p>
</div>
<div id="apr-02---us-tuition" class="section level1">
<h1>2018 Apr 02 - US Tuition</h1>
<p>Report can be found <a
href="2018-04-02-US-tuition/US_tuition.html">here</a></p>
<p>Summary: It is known that the cost of US university tuition fee has
increased in the past decades. The original data is somewhat limited in
scope since there are only <code>state</code>, <code>year</code> and
<code>cost</code> variables.</p>
<p>I am personally interested in knowing the cost of tuition fee vs the
GDP per capita in each US state. This would create about 10 scatter
plots (one for each year) for 50 states - kinda messy. So, I decided to
look at the <strong>tuition cost/GDP per capita ratio</strong> as a
measure of the affordability of university education in each state in
each year. Here, a higher ratio implies the education is getting more
expensive and thus less affordable. In order to summarise the 50 US
states, I further summarised the states into 8 geographical regions.</p>
<p>Interestingly, for most regions/states, the ratio is rather stable or
slightly increasing, suggesting that the tuition cost is somewhat in
pace with GDP increase. However, Southeast states seems to have a
steeper increase than othe regions.</p>
<p><strong>Key things that I learnt</strong>:</p>
<ul>
<li><code>ggpubr</code> provides very nice colour palettes (e.g. Lancet,
NEJM) that are somewhat in line with what these journals expect in their
publications.</li>
<li>The <code>ggiraph</code> package has received some very powerful
updates since the last time I used it in 2016. In some areas, I believe
it has better aesthetics/grammar than <code>plotly</code> (a default
interactive plotting package in my area).</li>
</ul>
<pre class="r"><code>complete_merge_data = readRDS("2018-04-02-US-tuition/complete_merge_data.RDS")
ratio_region_plot = complete_merge_data %>%
dplyr::mutate(Region = fct_reorder(Region, cost_gdp_ratio, .fun = median)) %>%
ggplot() +
geom_path_interactive(aes(x = year,
y = cost_gdp_ratio,
colour = Region,
group = State,
tooltip = State),
size = 2,
alpha = 0.5) +
stat_summary(aes(x = year,
y = cost_gdp_ratio,
colour = Region,
group = Region),
fun.y = "median", size = 2, geom = "path") +
facet_wrap(~Region, nrow = 1) +
scale_y_continuous(breaks = seq(0, 1, by = 0.1)) +
ggsci::scale_color_d3() +
labs(title = "Tuition cost - GDP per cap ratio, per US Region (interactive ggiraph plot)",
x = "Year",
y = "Tuition cost - GDP per cap ratio",
caption = "Thin line = state. Bold line = median ratio across all states per region") +
theme_classic(18) +
theme(legend.position = "bottom",
plot.title = element_text(hjust = 0.5),
panel.grid.major.x = element_blank(),
axis.text.x = element_text(angle = 90))</code></pre>
<pre><code>## Warning: The `fun.y` argument of `stat_summary()` is deprecated as of ggplot2 3.3.0.
## ℹ Please use the `fun` argument instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.</code></pre>
<pre><code>## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.</code></pre>
<pre class="r"><code>girafe(code = print(ratio_region_plot), width_svg = 15, height_svg = 6)</code></pre>
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points='966.00,82.27 988.84,85.18 1011.67,87.30 1034.50,83.36 1057.33,75.26' fill='none' stroke='#7F7F7F' stroke-opacity='0.5' stroke-width='4.27' stroke-linejoin='round' stroke-linecap='butt' title='Vermont'/>\n <polyline points='966.00,141.54 988.84,139.84 1011.67,141.12 1034.50,142.64 1057.33,139.42' fill='none' stroke='#7F7F7F' stroke-opacity='1' stroke-width='4.27' stroke-linejoin='round' stroke-linecap='butt'/>\n <\/g>\n <g clip-path='url(#svg_071065a1_404f_4c14_9d70_42794d6d0326_c10)'>\n <rect x='58.42' y='38.2' width='118.73' height='27.85' fill='#FFFFFF' fill-opacity='1' stroke='#000000' stroke-opacity='1' stroke-width='3.49' stroke-linejoin='round' stroke-linecap='round'/>\n <text x='64.2' y='57.29' font-size='10.8pt' font-family='Helvetica' fill='#1A1A1A' fill-opacity='1'>Rocky Mountain <\/text>\n <\/g>\n <g clip-path='url(#svg_071065a1_404f_4c14_9d70_42794d6d0326_c11)'>\n <rect x='186.12' y='38.2' width='118.73' height='27.85' fill='#FFFFFF' fill-opacity='1' 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West<\/text>\n <\/g>\n <g clip-path='url(#svg_071065a1_404f_4c14_9d70_42794d6d0326_c14)'>\n <rect x='569.21' y='38.2' width='118.73' height='27.85' fill='#FFFFFF' fill-opacity='1' stroke='#000000' stroke-opacity='1' stroke-width='3.49' stroke-linejoin='round' stroke-linecap='round'/>\n <text x='601.38' y='57.29' font-size='10.8pt' font-family='Helvetica' fill='#1A1A1A' fill-opacity='1'>Mideast <\/text>\n <\/g>\n <g clip-path='url(#svg_071065a1_404f_4c14_9d70_42794d6d0326_c15)'>\n <rect x='696.91' y='38.2' width='118.73' height='27.85' fill='#FFFFFF' fill-opacity='1' stroke='#000000' stroke-opacity='1' stroke-width='3.49' stroke-linejoin='round' stroke-linecap='round'/>\n <text x='721.87' y='57.29' font-size='10.8pt' font-family='Helvetica' fill='#1A1A1A' fill-opacity='1'>Southeast <\/text>\n <\/g>\n <g clip-path='url(#svg_071065a1_404f_4c14_9d70_42794d6d0326_c16)'>\n <rect x='824.6' y='38.2' width='118.73' height='27.85' fill='#FFFFFF' fill-opacity='1' stroke='#000000' stroke-opacity='1' stroke-width='3.49' stroke-linejoin='round' stroke-linecap='round'/>\n <text x='842.77' y='57.29' font-size='10.8pt' font-family='Helvetica' fill='#1A1A1A' fill-opacity='1'>Great Lakes <\/text>\n <\/g>\n <g clip-path='url(#svg_071065a1_404f_4c14_9d70_42794d6d0326_c17)'>\n <rect x='952.3' y='38.2' width='118.73' height='27.85' fill='#FFFFFF' fill-opacity='1' stroke='#000000' stroke-opacity='1' stroke-width='3.49' stroke-linejoin='round' stroke-linecap='round'/>\n <text x='966.87' y='57.29' font-size='10.8pt' font-family='Helvetica' fill='#1A1A1A' fill-opacity='1'>New England <\/text>\n <\/g>\n <g clip-path='url(#svg_071065a1_404f_4c14_9d70_42794d6d0326_c1)'>\n <polyline points='58.42,268.66 177.15,268.66' fill='none' stroke='#000000' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='72.12,273.15 72.12,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='94.95,273.15 94.95,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='117.78,273.15 117.78,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='140.62,273.15 140.62,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='163.45,273.15 163.45,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <text transform='translate(82.44,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2011<\/text>\n <text transform='translate(105.28,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2012<\/text>\n <text transform='translate(128.11,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2013<\/text>\n <text transform='translate(150.94,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2014<\/text>\n <text transform='translate(173.78,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2015<\/text>\n <polyline points='186.12,268.66 304.85,268.66' fill='none' stroke='#000000' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='199.82,273.15 199.82,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='222.65,273.15 222.65,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='245.48,273.15 245.48,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='268.32,273.15 268.32,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='291.15,273.15 291.15,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <text transform='translate(210.14,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2011<\/text>\n <text transform='translate(232.97,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2012<\/text>\n <text transform='translate(255.81,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2013<\/text>\n <text transform='translate(278.64,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2014<\/text>\n <text transform='translate(301.47,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2015<\/text>\n <polyline points='313.81,268.66 432.55,268.66' fill='none' stroke='#000000' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='327.51,273.15 327.51,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='350.35,273.15 350.35,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='373.18,273.15 373.18,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='396.01,273.15 396.01,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <polyline points='418.85,273.15 418.85,268.66' fill='none' stroke='#333333' stroke-opacity='1' stroke-width='1.75' stroke-linejoin='round' stroke-linecap='butt'/>\n <text transform='translate(337.84,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2011<\/text>\n <text transform='translate(360.67,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2012<\/text>\n <text transform='translate(383.50,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2013<\/text>\n <text transform='translate(406.34,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2014<\/text>\n <text transform='translate(429.17,308.76) rotate(-90.00)' font-size='10.8pt' font-family='Helvetica' fill='#4D4D4D' fill-opacity='1'>2015<\/text>\n <polyline points='441.51,268.66 560.24,268.66' fill='none' 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