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		<title>A really Cool data visualization: 3d globe in 2d space</title>
		<link>https://petaminds.com/a-really-cool-data-visualization-3d-globe-in-2d-space/</link>
					<comments>https://petaminds.com/a-really-cool-data-visualization-3d-globe-in-2d-space/#comments</comments>
		
		<dc:creator><![CDATA[Tung Nguyen]]></dc:creator>
		<pubDate>Mon, 11 Nov 2019 00:43:30 +0000</pubDate>
				<category><![CDATA[Android]]></category>
		<category><![CDATA[data science]]></category>
		<category><![CDATA[front-end]]></category>
		<category><![CDATA[Game Dev]]></category>
		<category><![CDATA[iOS]]></category>
		<category><![CDATA[Project]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[animation]]></category>
		<category><![CDATA[data]]></category>
		<category><![CDATA[Kotlin]]></category>
		<category><![CDATA[python]]></category>
		<category><![CDATA[visualization]]></category>
		<guid isPermaLink="false">https://petaminds.com/?p=1752</guid>

					<description><![CDATA[<p>While generating data in 3d space for manifold learning, I went across a problem of distributing points evenly on a sphere. It is a non-trivial problem but found a good enough solution for such placement. Interestingly, it ends up with a really cool animation effect when I decided to implement it on a mobile app. [&#8230;]</p>
<p>The post <a href="https://petaminds.com/a-really-cool-data-visualization-3d-globe-in-2d-space/">A really Cool data visualization: 3d globe in 2d space</a> appeared first on <a href="https://petaminds.com">Petamind</a>.</p>
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		<title>Data Visualization &#8211; Charts with Matplotlib</title>
		<link>https://petaminds.com/data-visualization-matplotlib-python-chart/</link>
					<comments>https://petaminds.com/data-visualization-matplotlib-python-chart/#respond</comments>
		
		<dc:creator><![CDATA[Tung Nguyen]]></dc:creator>
		<pubDate>Thu, 07 Nov 2019 03:41:09 +0000</pubDate>
				<category><![CDATA[data science]]></category>
		<category><![CDATA[Project]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[visualization]]></category>
		<category><![CDATA[data]]></category>
		<category><![CDATA[line]]></category>
		<category><![CDATA[matplotlib]]></category>
		<category><![CDATA[pair]]></category>
		<category><![CDATA[plot]]></category>
		<category><![CDATA[scatter]]></category>
		<category><![CDATA[stack]]></category>
		<guid isPermaLink="false">https://petaminds.com/?p=1738</guid>

					<description><![CDATA[<p>A common use for notebooks is data visualization using charts. It is easy with several charting tools available as Python imports. This article covers some common charts using matplotlib. Matplotlib Matplotlib&#160;is the most common charting package, see its&#160;documentation&#160;for details, and its&#160;examples&#160;for inspiration. Charting</p>
<p>The post <a href="https://petaminds.com/data-visualization-matplotlib-python-chart/">Data Visualization &#8211; Charts with Matplotlib</a> appeared first on <a href="https://petaminds.com">Petamind</a>.</p>
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