More ggplot Figures Peer Review

Macarena L. Fernandez Carro

Problem 1

Create the figure in the solution for Problem 1, using the data included in the R Markdown file.

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   3.4.4     ✔ 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(ggplot2)
library(dplyr)
library(psych)

## 
## Attaching package: 'psych'
## 
## The following objects are masked from 'package:ggplot2':
## 
##     %+%, alpha

library(corrgram)
library(GGally)

## Registered S3 method overwritten by 'GGally':
##   method from   
##   +.gg   ggplot2
## 
## Attaching package: 'GGally'
## 
## The following object is masked from 'package:corrgram':
## 
##     baseball

library(ggcorrplot)
library(ggalt)

## Registered S3 methods overwritten by 'ggalt':
##   method                  from   
##   grid.draw.absoluteGrob  ggplot2
##   grobHeight.absoluteGrob ggplot2
##   grobWidth.absoluteGrob  ggplot2
##   grobX.absoluteGrob      ggplot2
##   grobY.absoluteGrob      ggplot2

ggplot(dat1,
       aes(x = var1,
           y = var2)) +
  geom_point(aes(x = var1,
                 y = var2)) +
  geom_smooth() +
  labs(y = "Variable2",
       x = "Variable1" )

## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'

Problem 2

Create the figure in the solution for Problem 2, using the data included in the R Markdown file.

# 1. Check the relationships of my data

dat2 %>%
  pairs()

# 2. 

# custom function for density plot
my_density <- function(data, mapping, ...){
  ggplot(data = data, mapping = mapping) + 
    geom_density(fill = "cornflowerblue", ...)
}

# custom function for scatterplot
my_scatter <- function(data, mapping, ...){
  ggplot(data = data, mapping = mapping) + 
    geom_point(alpha = 0.5,
               color = "orange")
}

ggpairs(dat2, 
        lower=list(continuous = my_scatter), 
        diag = list(continuous = my_density)) 

Problem 3

Create the figure in the solution for Problem 3, using the data included in the R Markdown file.

cor(dat3)

##            var1       var2       var3
## var1  1.0000000  0.8785738 -0.9441741
## var2  0.8785738  1.0000000 -0.9650474
## var3 -0.9441741 -0.9650474  1.0000000

ggcorrplot(cor(dat3),
           type = "lower") +
  labs(title = "Correlations") +
  theme(plot.background = element_rect(fill = NA,
                                       color = "black"))

Problem 4

Create the figure in the solution for Problem 4, using the data included in the R Markdown file.

Problem 5

Create the figure in the solution for Problem 5, using the data included in the R Markdown file.

dat5.1 <- dat5 %>%
  arrange(var1)
dat5.1$names = factor(names,
                      levels = names)

ggplot(dat5.1,
       aes(x = names,
           y = var1)) +
  geom_segment(aes(xend = names),
               yend = 0,
               color = "darkgreen") +
  geom_point(color = "darkgreen") +
  ylim(c(0, 35)) +
  labs(y = "Variable 1")

Problem 6

Create the figure in the solution for Problem 6, using the data included in the R Markdown file.

ggplot(books_checked_out,
       aes(x = Time,
           y = Total,
           fill = Genre)) +
  geom_area() +
  labs(title = "Books Checked Out")

Problem 7

Create the figure in the solution for Problem 7, using the data included in the R Markdown file.

ggplot(books_checked_out2,
       aes(y = Genre,
           x = Time1,
           xend = Time5)) +
  geom_dumbbell(size = 0.5,
                size_x = 3,
                size_xend = 3,
                colour = "black",
                colour_x = "red",
                colour_xend = "purple")

## Warning: Using the `size` aesthetic with geom_segment was deprecated in ggplot2 3.4.0.
## ℹ Please use the `linewidth` aesthetic instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

Problem 8

Create the figure in the solution for Problem 8, using the data included in the R Markdown file.

library(RColorBrewer)

my_color<-brewer.pal(5,"Spectral")

pie(pie_dat,
    col = my_color)