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        <title><![CDATA[Stories by Maryam Rezapoor on Medium]]></title>
        <description><![CDATA[Stories by Maryam Rezapoor on Medium]]></description>
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            <title>Stories by Maryam Rezapoor on Medium</title>
            <link>https://medium.com/@rezmarya?source=rss-f1a2bca72a2a------2</link>
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            <title><![CDATA[Gender Inequality Index: How Different Countries are Doing?]]></title>
            <link>https://medium.com/@rezmarya/gender-inequality-index-how-different-countries-are-doing-3aaa60b16aba?source=rss-f1a2bca72a2a------2</link>
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            <category><![CDATA[gender-equality]]></category>
            <category><![CDATA[gender]]></category>
            <category><![CDATA[feminism]]></category>
            <category><![CDATA[data]]></category>
            <category><![CDATA[women]]></category>
            <dc:creator><![CDATA[Maryam Rezapoor]]></dc:creator>
            <pubDate>Sat, 12 May 2018 15:51:35 GMT</pubDate>
            <atom:updated>2018-05-13T01:35:39.610Z</atom:updated>
            <content:encoded><![CDATA[<p>The necessity of fighting inequalities with all power we’ve got is no longer in question. Inequality and concentration of power and opportunities among a narrow elite are part of a vicious circle. As inequalities become more widespread, non-elite groups have less and fewer opportunities and power to influence the subsequent distribution of power and privileges. With women comprising almost 50% of the population, gender inequality carries one of the highest priorities among all other inequalities.</p><p>Gender Inequality Index (GII) is a metric introduced by <a href="https://en.wikipedia.org/wiki/United_Nations_Development_Programme">United Nations Development Programme</a> (UNDP)in 2010 that shows the percentage of potential human development loss due to gender inequality and ranges from 0 representing “no lost opportunity” to 1 representing complete opportunity loss. The index was developed to cover the shortcomings of two previously developed indices: <a href="http://hdr.undp.org/en/content/gender-development-index-gdi">Gender Development Index</a> (GDI) and<a href="http://hdr.undp.org/en/2016-report"> Gender Empowerment Measure</a> (GEM), both developed in 1995. GII has five indicators that are classified into three dimensions: reproductive health, empowerment, and labor market participation.</p><figure><img alt="" src="https://cdn-images-1.medium.com/max/693/1*7M-a6cpKxv5vYGVOJDzgzg.png" /><figcaption>Source: Human Development Report Office.</figcaption></figure><p><strong>The relationship between Gender Inequality Index and Human Development:</strong></p><p>As shown in the graph below, high Gender Inequality (larger percentage of opportunity loss) correlates with lower human development. In other words, women are most marginalized in low human development countries. Can we tailor the message a bit and say that a gender-equal society is most likely a society with higher human development?</p><figure><img alt="" src="https://cdn-images-1.medium.com/max/572/1*Ev0Rjs0gUvoQpLGkjJv0Zw.png" /><figcaption>Source: Human Development Report Office.</figcaption></figure><p>Gender Inequality Index dataset can be found <a href="http://hdr.undp.org/en/composite/GII">here</a>. Let’s now dig into what my take from this dataset is.</p><p>The following source code shows my attempt to clean the data, calculate mean, minimum, and maximum of the dataset and deal with missing datapoints:</p><pre>data = data[[&#39;Country&#39;, &#39;1995&#39;, &#39;2000&#39;, &#39;2005&#39;, &#39;2010&#39;, &#39;2011&#39;, &#39;2012&#39;, &#39;2013&#39;, &#39;2014&#39;, &#39;2015&#39;]]<br>data = data.loc[~data[&quot;Country&quot;].isnull()]<br>filled_df = data.bfill(axis=1).ffill(axis=1)<br>data[&quot;Mean&quot;]=data.mean(axis=1)<br>data[&quot;Min&quot;]=data.min(axis=1)<br>data[&quot;Max&quot;]=data.max(axis=1)<br>data[&quot;Change&quot;] = filled_df[&quot;2015&quot;] - filled_df[&quot;1995&quot;]</pre><p>After cleaning this is how it looks:</p><p>(Remember that lower the GII is, the human development opportunity loss is also less.)</p><figure><img alt="" src="https://cdn-images-1.medium.com/max/740/1*1jKgK_Kp0nS9I57lWeasqQ.png" /></figure><p>I was curious to know how availability of data has changed over time, here is a great improvement on the number of countries with available GII data.</p><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*SfKPZGLX0CHoTEEACqYLGQ.jpeg" /></figure><p>Now here is a better news: The average of the countries’ GII index has improved over time:</p><figure><img alt="" src="https://cdn-images-1.medium.com/max/700/1*DIWZ-ntzyYp1IYTaSQJnOQ.jpeg" /></figure><p>Want to know which countries have the most improved GII index from 1995 to 2015?</p><figure><img alt="" src="https://cdn-images-1.medium.com/max/700/1*leHoau2XKUAHGXBrLe9lbA.jpeg" /></figure><p>It is very interesting that Saudi Arabia has had such a great improvement in just one year (from 2011 to 2012). If you know what happened in the country that triggered such an improvement please share it under this post. United Arab Emirates’ GII metric also improved significantly in 5 years but slightly worsen from 2005 to 2015. Maldives, Turkey, and Estonia have apparently implemented some policies to improve the index nice and steady. I hope that by visualizing this information and share it on the large scale we can motivate policymakers and governments of countries around the world to invest more and fight gender inequality harder.</p><p>And finally, here is the glance into the world’s map and the GII index of different countries ranging from dark blue (the best) to dark orange (the worst). And if you want to know which five countries are doing the best and which ones need to work harder, see the graph below.</p><figure><img alt="" src="https://cdn-images-1.medium.com/max/700/1*fhEQGOJ_-XrZBJJ4VpNKIA.jpeg" /></figure><figure><img alt="" src="https://cdn-images-1.medium.com/max/870/1*IyyqjArffjlvmgIU_EIQ7A.png" /></figure><p>This dataset definitely has lots of potentials for further analyses. If you are interested to play with this dataset, you can find my source code on <a href="https://github.com/MaryamRez/My-Gender-Equality-Project/blob/master/Code/01_Inequality.ipynb">my Github page</a>. Stay tuned for my next analysis.</p><p><strong>Thank you.</strong></p><img src="https://medium.com/_/stat?event=post.clientViewed&referrerSource=full_rss&postId=3aaa60b16aba" width="1" height="1" alt="">]]></content:encoded>
        </item>
        <item>
            <title><![CDATA[A Look into Public Datasets for Gender Equality]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@rezmarya/a-look-into-public-datasets-for-gender-equality-305c88d8d90b?source=rss-f1a2bca72a2a------2"><img src="https://cdn-images-1.medium.com/max/1245/1*RfydJu4z5YjTDc6RqZdW9w.png" width="1245"></a></p><p class="medium-feed-snippet">Based on a report published by McKinsey Global Institute, the volume of available data doubles every three years.</p><p class="medium-feed-link"><a href="https://medium.com/@rezmarya/a-look-into-public-datasets-for-gender-equality-305c88d8d90b?source=rss-f1a2bca72a2a------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://medium.com/@rezmarya/a-look-into-public-datasets-for-gender-equality-305c88d8d90b?source=rss-f1a2bca72a2a------2</link>
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            <category><![CDATA[data-science]]></category>
            <category><![CDATA[open-data]]></category>
            <category><![CDATA[data-analysis]]></category>
            <category><![CDATA[data-visualization]]></category>
            <category><![CDATA[gender-equality]]></category>
            <dc:creator><![CDATA[Maryam Rezapoor]]></dc:creator>
            <pubDate>Tue, 08 May 2018 03:30:20 GMT</pubDate>
            <atom:updated>2018-05-08T03:30:20.602Z</atom:updated>
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        <item>
            <title><![CDATA[The Importance of Data and its Presentation in Tackling Women Issues]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@rezmarya/the-importance-of-data-and-its-presentation-in-tackling-women-issues-e0e01f598eeb?source=rss-f1a2bca72a2a------2"><img src="https://cdn-images-1.medium.com/max/720/1*Lrjg4upPAjXIN8eaLrzVpg.jpeg" width="720"></a></p><p class="medium-feed-snippet">&#x201C;Imagine the gradual formation of a riverbed. The initial flow of water might be completely random &#x2014; there are no preferred routes in the&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/@rezmarya/the-importance-of-data-and-its-presentation-in-tackling-women-issues-e0e01f598eeb?source=rss-f1a2bca72a2a------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://medium.com/@rezmarya/the-importance-of-data-and-its-presentation-in-tackling-women-issues-e0e01f598eeb?source=rss-f1a2bca72a2a------2</link>
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            <category><![CDATA[gender-equality]]></category>
            <category><![CDATA[women]]></category>
            <category><![CDATA[data-analysis]]></category>
            <category><![CDATA[domestic-violence]]></category>
            <category><![CDATA[feminism]]></category>
            <dc:creator><![CDATA[Maryam Rezapoor]]></dc:creator>
            <pubDate>Wed, 02 May 2018 03:57:24 GMT</pubDate>
            <atom:updated>2018-05-02T03:57:24.244Z</atom:updated>
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