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19 changes: 9 additions & 10 deletions StudentNotebooks/Assignment01/balajy-assignment1-f24.Rmd
Expand Up @@ -4,11 +4,11 @@ subtitle: "DAR Assignment 1 (Fall 2024)"
author: "Yashas Balaji"
date: "`r format(Sys.time(), '%d %B %Y')`"
output:
pdf_document: default
html_document:
toc: true
number_sections: true
df_print: paged
pdf_document: default
---
```{r setup, include=FALSE}
# REQUIRE R PACKAGE INSTALLATIONS
Expand Down Expand Up @@ -217,9 +217,11 @@ Here is the MARS PIXL data. Take note of the variables, their types, and distriu
# Saved LIBS data with locations added
# NOTE: Use course directory version during the semester
pixl.df<- readRDS("~/DAR-Mars-F24/Data/samples_pixl_wide.Rds")
# pixl.df<- readRDS("/academics/MATP-4910-F24/DAR-Mars-F24/Data/samples_pixl_wide.Rds")
# Use this version to use downloaded data from github
pixl.df <- readRDS("~/DAR-Mars-F24/Data/samples_pixl_wide.Rds")
# pixl.df <- readRDS("~/DAR-Mars-F24/Data/samples_pixl_wide.Rds")
# convert location to a number
pixl.df$location <- as.numeric(pixl.df$location )
Expand Down Expand Up @@ -342,19 +344,16 @@ ggbiplot::ggbiplot(pixl_trim.mat.pca,

Add a description of each cluster here in your own words.

Describe Cluster 1: _Your description here_
Describe Cluster 1: Cluster 1, the smallest cluster seems to be mainly igneous rock and is highly composed of Silicone Dioxide (SiO2)

Describe Cluster 2: _Your description here_
Describe Cluster 2: Cluster 2, the largest cluster seems to be mainly comprised of sedimentary rock, and is highly composed of SiO2, SO3, Mgo, and FeO-T

Describe Cluster 3: _Your description here_
Describe Cluster 3: Cluster 3, is also composed of igneous rock and is highly composed of SiO2, Mgo and FeO-T


What do the clustering and PCA results tell us about the data detected by the M20 PIXL experiment? _Feel free to add graphs or analyses to support your conclusions._
What do the clustering and PCA results tell us about the data detected by the M20 PIXL experiment?

```{r}
# Student's code for graphs and analysis here!
```
The clustering tells us what groups of rock has higher concentrations of certain molecules in the rock, and the pca analysis gives us the explained variance of the sample. Additionally the plot having the type of rock was helpful in telling us what rocks each cluster had.

## SAVE, COMMIT and PUSH YOUR CHANGES!

Expand Down
18 changes: 10 additions & 8 deletions StudentNotebooks/Assignment01/balajy-assignment1-f24.html
Expand Up @@ -11,7 +11,7 @@

<meta name="author" content="Yashas Balaji" />

<meta name="date" content="2024-08-28" />
<meta name="date" content="2024-09-03" />

<title>RPI github and Mars 2020 PIXL Example Notebook:</title>

Expand Down Expand Up @@ -167,7 +167,7 @@
<h1 class="title toc-ignore">RPI github and Mars 2020 PIXL Example Notebook:</h1>
<h3 class="subtitle">DAR Assignment 1 (Fall 2024)</h3>
<h4 class="author">Yashas Balaji</h4>
<h4 class="date">28 August 2024</h4>
<h4 class="date">03 September 2024</h4>

</div>

Expand Down Expand Up @@ -375,9 +375,11 @@ <h2><span class="header-section-number">3.1</span> Load the PIXL Data and displa
<pre class="r"><code># Saved LIBS data with locations added

# NOTE: Use course directory version during the semester
pixl.df&lt;- readRDS(&quot;~/DAR-Mars-F24/Data/samples_pixl_wide.Rds&quot;)

# pixl.df&lt;- readRDS(&quot;/academics/MATP-4910-F24/DAR-Mars-F24/Data/samples_pixl_wide.Rds&quot;)
# Use this version to use downloaded data from github
pixl.df &lt;- readRDS(&quot;~/DAR-Mars-F24/Data/samples_pixl_wide.Rds&quot;)
# pixl.df &lt;- readRDS(&quot;~/DAR-Mars-F24/Data/samples_pixl_wide.Rds&quot;)

# convert location to a number
pixl.df$location &lt;- as.numeric(pixl.df$location )
Expand Down Expand Up @@ -555,11 +557,11 @@ <h2><span class="header-section-number">4.4</span> Create a PCA Biplot using ggb
<div id="answer-these-questions" class="section level2" number="4.5">
<h2><span class="header-section-number">4.5</span> ANSWER THESE QUESTIONS!</h2>
<p>Add a description of each cluster here in your own words.</p>
<p>Describe Cluster 1: <em>Your description here</em></p>
<p>Describe Cluster 2: <em>Your description here</em></p>
<p>Describe Cluster 3: <em>Your description here</em></p>
<p>What do the clustering and PCA results tell us about the data detected by the M20 PIXL experiment? <em>Feel free to add graphs or analyses to support your conclusions.</em></p>
<pre class="r"><code># Student&#39;s code for graphs and analysis here!</code></pre>
<p>Describe Cluster 1: Cluster 1, the smallest cluster seems to be mainly igneous rock and is highly composed of Silicone Dioxide (SiO2)</p>
<p>Describe Cluster 2: Cluster 2, the largest cluster seems to be mainly comprised of sedimentary rock, and is highly composed of SiO2, SO3, Mgo, and FeO-T</p>
<p>Describe Cluster 3: Cluster 3, is also composed of igneous rock and is highly composed of SiO2, Mgo and FeO-T</p>
<p>What do the clustering and PCA results tell us about the data detected by the M20 PIXL experiment?</p>
<p>The clustering tells us what groups of rock has higher concentrations of certain molecules in the rock, and the pca analysis gives us the explained variance of the sample. Additionally the plot having the type of rock was helpful in telling us what rocks each cluster had.</p>
</div>
<div id="save-commit-and-push-your-changes" class="section level2" number="4.6">
<h2><span class="header-section-number">4.6</span> SAVE, COMMIT and PUSH YOUR CHANGES!</h2>
Expand Down
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