DslabsHw

library("dslabs")

Warning: package 'dslabs' was built under R version 4.4.1

data(package="dslabs")
list.files(system.file("script", package = "dslabs"))

 [1] "make-admissions.R"                   
 [2] "make-brca.R"                         
 [3] "make-brexit_polls.R"                 
 [4] "make-calificaciones.R"               
 [5] "make-death_prob.R"                   
 [6] "make-divorce_margarine.R"            
 [7] "make-gapminder-rdas.R"               
 [8] "make-greenhouse_gases.R"             
 [9] "make-historic_co2.R"                 
[10] "make-mice_weights.R"                 
[11] "make-mnist_127.R"                    
[12] "make-mnist_27.R"                     
[13] "make-movielens.R"                    
[14] "make-murders-rda.R"                  
[15] "make-na_example-rda.R"               
[16] "make-nyc_regents_scores.R"           
[17] "make-olive.R"                        
[18] "make-outlier_example.R"              
[19] "make-polls_2008.R"                   
[20] "make-polls_us_election_2016.R"       
[21] "make-pr_death_counts.R"              
[22] "make-reported_heights-rda.R"         
[23] "make-research_funding_rates.R"       
[24] "make-stars.R"                        
[25] "make-temp_carbon.R"                  
[26] "make-tissue-gene-expression.R"       
[27] "make-trump_tweets.R"                 
[28] "make-weekly_us_contagious_diseases.R"
[29] "save-gapminder-example-csv.R"        

data("stars")
library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.1     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(ggthemes)

Warning: package 'ggthemes' was built under R version 4.4.1

library(ggrepel)

Warning: package 'ggrepel' was built under R version 4.4.1

str(stars)

'data.frame':   96 obs. of  4 variables:
 $ star     : Factor w/ 95 levels "*40EridaniA",..: 87 85 48 38 33 92 49 79 77 47 ...
 $ magnitude: num  4.8 1.4 -3.1 -0.4 4.3 0.5 -0.6 -7.2 2.6 -5.7 ...
 $ temp     : int  5840 9620 7400 4590 5840 9900 5150 12140 6580 3200 ...
 $ type     : chr  "G" "A" "F" "K" ...

write_csv(stars,"stars.csv",na="")

mult <- stars |>
  ggplot(aes(x=magnitude, y=temp, color=type)) +
  geom_point(size=2) +
  scale_fill_discrete(name = "Type") + 
  scale_color_manual(values = c("A" = "#58508d", "B" = "#5096d3", "DA" = "#8a508f", "DB" = "#dc4093", "DF" = "#d164bf", "F" = "#ff6361", "G" = "#e4395a", "K" = "#ffa600","M" = "#41d53c", "O" = "#233d83" )) +
  labs(x="Magnitude", y="Temperature(°C)", title="Temperature vs Magnitude of Stars", col = "Spectral Type")+
  theme(text=element_text(family="NimbusSan")) +
  theme_dark() 
mult 

I created a scatter-plot using the Stars data set displaying the relationship between a star’s temperature and its magnitude. The plot shows a really interesting non-linear regression that I wanted to show with geom_smooth, but I was unable to create a singular negative exponential curve, so I ultimately deleted that line of code.