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	<title>Comments for David B. Sparks</title>
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	<link>http://dsparks.wordpress.com</link>
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	<lastBuildDate>Fri, 11 May 2012 12:56:34 +0000</lastBuildDate>
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		<title>Comment on Isarithmic Maps of Public Opinion Data by Nicholas</title>
		<link>http://dsparks.wordpress.com/2011/10/24/isarithmic-maps-of-public-opinion-data/#comment-154</link>
		<dc:creator><![CDATA[Nicholas]]></dc:creator>
		<pubDate>Fri, 11 May 2012 12:56:34 +0000</pubDate>
		<guid isPermaLink="false">http://dsparks.wordpress.com/?p=376#comment-154</guid>
		<description><![CDATA[Great work.  I don&#039;t know if you are still working on this, but some of the color palettes work better than others.  I think Red/Blue is better than Red/Green.  One of the problems is that the univariate map is now a bivariate map, and it is difficult to perceive bivariate data through color alone.  There is quite a bit of cognitive research on how we perceive color.  The bottom line is, it&#039;s difficult; but some color spaces are better than others.  RGB is really bad.  HSV is better.  LAB is probably better, yet.  But the trick is to get one perceptual axis of color (such as hue) to map into income/or votes, and another perceptual axis of color (such as value) to map into population density.  The univariate RColorBrewer palettes aren&#039;t designed for crossing with a second data dimension.
I&#039;d also suggest trying fewer color bins, especially on the pop density axis.  It might reduce the cognitive load of the maps, making it easier to compare both data value and density separately.  Or it might not!  I don&#039;t know.
Great stuff.]]></description>
		<content:encoded><![CDATA[<p>Great work.  I don&#8217;t know if you are still working on this, but some of the color palettes work better than others.  I think Red/Blue is better than Red/Green.  One of the problems is that the univariate map is now a bivariate map, and it is difficult to perceive bivariate data through color alone.  There is quite a bit of cognitive research on how we perceive color.  The bottom line is, it&#8217;s difficult; but some color spaces are better than others.  RGB is really bad.  HSV is better.  LAB is probably better, yet.  But the trick is to get one perceptual axis of color (such as hue) to map into income/or votes, and another perceptual axis of color (such as value) to map into population density.  The univariate RColorBrewer palettes aren&#8217;t designed for crossing with a second data dimension.<br />
I&#8217;d also suggest trying fewer color bins, especially on the pop density axis.  It might reduce the cognitive load of the maps, making it easier to compare both data value and density separately.  Or it might not!  I don&#8217;t know.<br />
Great stuff.</p>
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		<title>Comment on Isarithmic Maps of Public Opinion Data by Christi</title>
		<link>http://dsparks.wordpress.com/2011/10/24/isarithmic-maps-of-public-opinion-data/#comment-153</link>
		<dc:creator><![CDATA[Christi]]></dc:creator>
		<pubDate>Fri, 04 May 2012 14:27:03 +0000</pubDate>
		<guid isPermaLink="false">http://dsparks.wordpress.com/?p=376#comment-153</guid>
		<description><![CDATA[David Sparks has an amazing eye for presenting data.....Beautifully done]]></description>
		<content:encoded><![CDATA[<p>David Sparks has an amazing eye for presenting data&#8230;..Beautifully done</p>
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		<title>Comment on Isarithmic Maps of Public Opinion Data by Weekly links for March 18 &#171; God plays dice</title>
		<link>http://dsparks.wordpress.com/2011/10/24/isarithmic-maps-of-public-opinion-data/#comment-152</link>
		<dc:creator><![CDATA[Weekly links for March 18 &#171; God plays dice]]></dc:creator>
		<pubDate>Mon, 19 Mar 2012 00:07:21 +0000</pubDate>
		<guid isPermaLink="false">http://dsparks.wordpress.com/?p=376#comment-152</guid>
		<description><![CDATA[[...] Isarithmic maps of public opinion data. [...]]]></description>
		<content:encoded><![CDATA[<p>[...] Isarithmic maps of public opinion data. [...]</p>
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		<title>Comment on Isarithmic Maps of Public Opinion Data by Tom</title>
		<link>http://dsparks.wordpress.com/2011/10/24/isarithmic-maps-of-public-opinion-data/#comment-151</link>
		<dc:creator><![CDATA[Tom]]></dc:creator>
		<pubDate>Wed, 14 Mar 2012 13:08:19 +0000</pubDate>
		<guid isPermaLink="false">http://dsparks.wordpress.com/?p=376#comment-151</guid>
		<description><![CDATA[Having been raised on Cleveland&#039;s _Visualizing Data_, I have an extremely strong preference for easy interpretation over prettiness. Go with the white background]]></description>
		<content:encoded><![CDATA[<p>Having been raised on Cleveland&#8217;s _Visualizing Data_, I have an extremely strong preference for easy interpretation over prettiness. Go with the white background</p>
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		<title>Comment on Isarithmic Maps of Public Opinion Data by D.O.</title>
		<link>http://dsparks.wordpress.com/2011/10/24/isarithmic-maps-of-public-opinion-data/#comment-150</link>
		<dc:creator><![CDATA[D.O.]]></dc:creator>
		<pubDate>Tue, 13 Mar 2012 22:27:55 +0000</pubDate>
		<guid isPermaLink="false">http://dsparks.wordpress.com/?p=376#comment-150</guid>
		<description><![CDATA[Great graphics!
I do not agree with &quot;white for low density&quot; approach. Not sure which is better, but there is a whole series of the photographs of Earth or its parts showing the degree of development by luminocity at night. Dark regions naturally imply less development, which for U.S. most strongly correlates with low density.]]></description>
		<content:encoded><![CDATA[<p>Great graphics!<br />
I do not agree with &#8220;white for low density&#8221; approach. Not sure which is better, but there is a whole series of the photographs of Earth or its parts showing the degree of development by luminocity at night. Dark regions naturally imply less development, which for U.S. most strongly correlates with low density.</p>
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		<title>Comment on Isarithmic Maps of Public Opinion Data by C. Holmberg</title>
		<link>http://dsparks.wordpress.com/2011/10/24/isarithmic-maps-of-public-opinion-data/#comment-149</link>
		<dc:creator><![CDATA[C. Holmberg]]></dc:creator>
		<pubDate>Tue, 13 Mar 2012 19:06:18 +0000</pubDate>
		<guid isPermaLink="false">http://dsparks.wordpress.com/?p=376#comment-149</guid>
		<description><![CDATA[I agree on all points, particularly: white background.]]></description>
		<content:encoded><![CDATA[<p>I agree on all points, particularly: white background.</p>
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		<title>Comment on Isarithmic Maps of Public Opinion Data by Brad</title>
		<link>http://dsparks.wordpress.com/2011/10/24/isarithmic-maps-of-public-opinion-data/#comment-148</link>
		<dc:creator><![CDATA[Brad]]></dc:creator>
		<pubDate>Tue, 13 Mar 2012 19:01:20 +0000</pubDate>
		<guid isPermaLink="false">http://dsparks.wordpress.com/?p=376#comment-148</guid>
		<description><![CDATA[I just wanted to say that besides putting up a lot of interesting data in a very useful way, these maps are absolutely stunning to behold. The party identification map with the black background is stunning. I would frame it and hang it up in my house.]]></description>
		<content:encoded><![CDATA[<p>I just wanted to say that besides putting up a lot of interesting data in a very useful way, these maps are absolutely stunning to behold. The party identification map with the black background is stunning. I would frame it and hang it up in my house.</p>
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		<title>Comment on Isarithmic Maps of Public Opinion Data by kerokan</title>
		<link>http://dsparks.wordpress.com/2011/10/24/isarithmic-maps-of-public-opinion-data/#comment-147</link>
		<dc:creator><![CDATA[kerokan]]></dc:creator>
		<pubDate>Tue, 13 Mar 2012 18:46:24 +0000</pubDate>
		<guid isPermaLink="false">http://dsparks.wordpress.com/?p=376#comment-147</guid>
		<description><![CDATA[I would go for white. It is much easier for me to interpret white area as sparse. Good job, by the way.]]></description>
		<content:encoded><![CDATA[<p>I would go for white. It is much easier for me to interpret white area as sparse. Good job, by the way.</p>
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	<item>
		<title>Comment on Isarithmic Maps of Public Opinion Data by Localized Comparisons: Idiopleth Maps? &#124; Civil Statistician</title>
		<link>http://dsparks.wordpress.com/2011/10/24/isarithmic-maps-of-public-opinion-data/#comment-146</link>
		<dc:creator><![CDATA[Localized Comparisons: Idiopleth Maps? &#124; Civil Statistician]]></dc:creator>
		<pubDate>Fri, 09 Mar 2012 22:38:06 +0000</pubDate>
		<guid isPermaLink="false">http://dsparks.wordpress.com/?p=376#comment-146</guid>
		<description><![CDATA[[...] let the viewer play with how the colors are done. And David Sparks has done related work, trying to show confidence/uncertainty on maps based on smoothed data, rather than drawing areas separately as in a choropleth. I like this approach for looking at [...]]]></description>
		<content:encoded><![CDATA[<p>[...] let the viewer play with how the colors are done. And David Sparks has done related work, trying to show confidence/uncertainty on maps based on smoothed data, rather than drawing areas separately as in a choropleth. I like this approach for looking at [...]</p>
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		<title>Comment on Choropleth tutorial and regression coefficient plots by d sparks</title>
		<link>http://dsparks.wordpress.com/2011/02/21/choropleth-tutorial-and-regression-coefficient-plots/#comment-145</link>
		<dc:creator><![CDATA[d sparks]]></dc:creator>
		<pubDate>Wed, 08 Feb 2012 01:32:42 +0000</pubDate>
		<guid isPermaLink="false">http://dsparks.wordpress.com/?p=320#comment-145</guid>
		<description><![CDATA[On nice thing about Dr. Wickham&#039;s ggplot2 package is that it makes faceting very straightforward (see &lt;a href=&quot;http://had.co.nz/ggplot2/facet_grid.html&quot; title=&quot;facet_grid&quot; rel=&quot;nofollow&quot;&gt;facet_grid&lt;/a&gt;). If some time becomes available, I might take the opportunity to put together a tutorial on it -- I have some data for which the small multiples approach would be useful.]]></description>
		<content:encoded><![CDATA[<p>On nice thing about Dr. Wickham&#8217;s ggplot2 package is that it makes faceting very straightforward (see <a href="http://had.co.nz/ggplot2/facet_grid.html" title="facet_grid" rel="nofollow">facet_grid</a>). If some time becomes available, I might take the opportunity to put together a tutorial on it &#8212; I have some data for which the small multiples approach would be useful.</p>
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