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<h1 class="code-line" data-line-start=0 data-line-end=1><a id="GDP_and_Life_Expectancy_Analysis_for_6_Countries_20002015_0"></a>GDP and Life Expectancy Analysis for 6 Countries (2000-2015)</h1>
<p class="has-line-data" data-line-start="3" data-line-end="4">This is a post analysing the how the life expectancy and GDP has changed over time for Chile, China, Germany, Mexico, the USA and Zimbabwe.</p>
<p class="has-line-data" data-line-start="5" data-line-end="6">The data for this report is from the years 2000 to 2015 inclusively.</p>
<p class="has-line-data" data-line-start="7" data-line-end="8"><img src="https://i.imgur.com/ax3sfOw.png" alt="image"></p>
<p class="has-line-data" data-line-start="9" data-line-end="10">We can make a few conclusions from this violin plot. The first is that deviation/spread of the Life Expectancy over time of each country is relatively compact, with the interquartile range spanning only a couple of years, which conveys only a small change over time. Zimbabwe is an exception to this however, with even their interquartile range spanning over a decade and the whole dataset being over 20 years apart, suggesting a much wider change. The second conclusion that is clear to see, is that all countries apart from Zimbabwe have a high Life Expectancy, both to begin with and at the end of the timeframe we are looking at.</p>
<p class="has-line-data" data-line-start="11" data-line-end="12"><img src="https://i.imgur.com/nBk6ZFB.png" alt="image"></p>
<p class="has-line-data" data-line-start="13" data-line-end="14">Next, the facet grid of scatter graphs above conveys the change in GDP year on year for each of our 6 countries, represented against the Life Expectancy. Again, as identified before, all countries apart from Zimbabwe start with a high Life Expectancy which only sees a slight increase over the timeframe. The same cannot be said for GDP, with China, followed by USA, making the largest leaps in GDP, both seeing around $1tn of growth. Germany sees some growth, but not to the same level as China or USA, with Mexico and Chile seeing a slight growth. Zimbabwe has a much smaller increase in GDP, but their Life Expectancy grows by the largest amount.</p>
<p class="has-line-data" data-line-start="15" data-line-end="16">There is enough of a relationship to say that the increase in GDP correlates with an increase in Life Expectancy, but the rate at which a country’s GDP grows is much larger than the increase in Life Expectancy. For example, USA saw an increase of around +75% to their GDP in the 15 years, but their life expectancy only grew around 5%.</p>
<p class="has-line-data" data-line-start="17" data-line-end="18">For the first 5 countries, this is most likely due to a high standard of living being present at even the earliest point in the data (2000). However Zimbabwe is only just seeing their standard of living increase to that of modern society, so they are seeing greater leaps in their Life Expectancy.</p>
<p class="has-line-data" data-line-start="19" data-line-end="20">Studys report the main reasons for China’s increase in GDP as being large scale capital investment (financed by both domestic savings and foreign investment) and being world leaders in productivity growth during this timeframe. Source: <a href="https://www.everycrsreport.com/reports/RL33534.html">https://www.everycrsreport.com/reports/RL33534.html</a></p>
<p class="has-line-data" data-line-start="21" data-line-end="22"><img src="https://i.imgur.com/1vScnqv.png" alt="image"> <img src="https://i.imgur.com/UXlHf6u.png" alt="image"></p>
<p class="has-line-data" data-line-start="23" data-line-end="24">This pair of line graph facet grids reinforces our conclusions above. Showing the same trend in data but with each country isolated from one another.</p>
<h1 class="code-line" data-line-start=25 data-line-end=26><a id="Conclusion_and_Graph_Selection_25"></a>Conclusion and Graph Selection</h1>
<p class="has-line-data" data-line-start="26" data-line-end="27">We explored the use of several graph types to convey our message. A violin graph is a fantastic choice to see the spread of values in our dataset, being a stronger choice than a histogram due to the smoother lines and ability to borrow features from a box plot diagram. This makes it a great choice to make several conclusions from a high level look at the data, as shown by the points we made.</p>
<p class="has-line-data" data-line-start="28" data-line-end="29">When looking more in depth at the data over time, while a scatter graph does allow for good comparison of each countries relationship to one another (for a single given year), a line graph allows for easier recognition of trends over time.</p>
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