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	<title>Plots and Charts &#8211; NIRPY Research</title>
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	<description>Statistical learning and chemometrics in Python</description>
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		<title>Updates and additions to the PLS Regression code</title>
		<link>https://nirpyresearch.com/updates-pls-regression/</link>
		
		<dc:creator><![CDATA[Daniel Pelliccia]]></dc:creator>
		<pubDate>Sat, 29 Apr 2023 09:28:45 +0000</pubDate>
				<category><![CDATA[Regression]]></category>
		<category><![CDATA[Partial Least Squares Regression]]></category>
		<category><![CDATA[Plots and Charts]]></category>
		<guid isPermaLink="false">https://nirpyresearch.com/?p=2967</guid>

					<description><![CDATA[<img width="666" height="499" src="https://nirpyresearch.com/wp-content/uploads/2023/04/PLS_updates.jpg" class="webfeedsFeaturedVisual wp-post-image" alt="PLS regression" style="display: block; margin-bottom: 10px; clear: both; max-width: 100%;" decoding="async" fetchpriority="high" />Updated code and additional utility scripts for PLS regression. Will keep it updated as we go.]]></description>
		
		
		
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		<title>The PCA correlation circle</title>
		<link>https://nirpyresearch.com/pca-correlation-circle/</link>
		
		<dc:creator><![CDATA[Daniel Pelliccia]]></dc:creator>
		<pubDate>Sat, 03 Sep 2022 09:23:48 +0000</pubDate>
				<category><![CDATA[Plots and Charts]]></category>
		<category><![CDATA[Data Operations and Plotting]]></category>
		<category><![CDATA[Principal Components Analysis]]></category>
		<guid isPermaLink="false">https://nirpyresearch.com/?p=2771</guid>

					<description><![CDATA[<img width="666" height="499" src="https://nirpyresearch.com/wp-content/uploads/2022/08/PCACorrelationCircle.jpg" class="webfeedsFeaturedVisual wp-post-image" alt="" style="display: block; margin-bottom: 10px; clear: both; max-width: 100%;" decoding="async" />The PCA correlation circle is a useful tool to visually display the correlation between spectral bands and principal components. The correlation can be quantified through the Euclidean distance and used to colour code spectral bands for further insight.]]></description>
		
		
		
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		<title>Aquagrams with Python and Matplotlib</title>
		<link>https://nirpyresearch.com/aquagrams-python-matplotlib/</link>
		
		<dc:creator><![CDATA[Daniel Pelliccia]]></dc:creator>
		<pubDate>Sat, 09 Jul 2022 02:05:24 +0000</pubDate>
				<category><![CDATA[Data Operations and Plotting]]></category>
		<category><![CDATA[Plots and Charts]]></category>
		<guid isPermaLink="false">https://nirpyresearch.com/?p=2677</guid>

					<description><![CDATA[<img width="666" height="499" src="https://nirpyresearch.com/wp-content/uploads/2022/07/aquagram_example.png" class="webfeedsFeaturedVisual wp-post-image" alt="Aquagrams with Python and Matplotlib" style="display: block; margin-bottom: 10px; clear: both; max-width: 100%;" decoding="async" />Aquagrams are diagrams charting the relative strength of the NIR reflectance or absorbance of specific bands in water-based systems. Here's an example code to plot an aquagram using Matplotlib.]]></description>
		
		
		
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		<title>NIR data correlograms with Seaborn in Python</title>
		<link>https://nirpyresearch.com/nir-data-correlograms-seaborn-python/</link>
		
		<dc:creator><![CDATA[Daniel Pelliccia]]></dc:creator>
		<pubDate>Thu, 03 Jan 2019 07:50:38 +0000</pubDate>
				<category><![CDATA[Data Operations and Plotting]]></category>
		<category><![CDATA[Plots and Charts]]></category>
		<guid isPermaLink="false">https://www.idtools.com.au/?p=1535</guid>

					<description><![CDATA[<img width="680" height="272" src="https://nirpyresearch.com/wp-content/uploads/2019/01/NIR-data-correlograms-Seaborn-Python-1024x410.jpg" class="webfeedsFeaturedVisual wp-post-image" alt="NIR data correlograms with Seaborn in Python" style="display: block; margin-bottom: 10px; clear: both; max-width: 100%;" decoding="async" loading="lazy" />Exploratory analysis is an essential part of data analysis. Learn a handy way to explore your dataset with NIR data correlograms with Seaborn in Python.]]></description>
		
		
		
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