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		<title>Advanced python: collections</title>
		<link>https://petaminds.com/advanced-python-part-3/</link>
					<comments>https://petaminds.com/advanced-python-part-3/#respond</comments>
		
		<dc:creator><![CDATA[Tung Nguyen]]></dc:creator>
		<pubDate>Mon, 29 Jun 2020 01:01:42 +0000</pubDate>
				<category><![CDATA[data science]]></category>
		<category><![CDATA[front-end]]></category>
		<category><![CDATA[Project]]></category>
		<category><![CDATA[advanced]]></category>
		<category><![CDATA[collections]]></category>
		<category><![CDATA[counter]]></category>
		<category><![CDATA[defaultdict]]></category>
		<category><![CDATA[deque]]></category>
		<category><![CDATA[namedtuple]]></category>
		<category><![CDATA[python]]></category>
		<guid isPermaLink="false">https://petaminds.com/?p=2450</guid>

					<description><![CDATA[<p>In&#160;part 2, we introduced advanced python knowledge with built-in functions and other useful tools for sequence iteration, data transformation. Advanced python part 3 will continue with collections to manipulate our data. Named tuple Suppose we want to define a data structure&#160;to represent a geometric point on a typical x and y-axis. We could easily do [&#8230;]</p>
<p>The post <a href="https://petaminds.com/advanced-python-part-3/">Advanced python: collections</a> appeared first on <a href="https://petaminds.com">Petamind</a>.</p>
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