Lab 01 - Hello R!

due Monday January 17 11:59 PM

Load Packages

library(tidyverse)
library(datasauRus)

Exercise 1

This data frame has 1846 rows and 3 columms. variables included in the data fram are appreances.

Exercise 2

dino_data <- datasaurus_dozen %>%
  filter(dataset == "dino")
ggplot(data = dino_data, mapping = aes(x = x, y = y)) + 
  geom_point()

dino_data %>%
  summarize(r = cor(x, y))

## # A tibble: 1 × 1
##         r
##     <dbl>
## 1 -0.0645

-0.0645

Exercise 3

-0.0630

star_data <- datasaurus_dozen %>%
  filter(dataset == "star")
ggplot(data = star_data, mapping = aes(x = x, y = y)) +
  geom_point()

star_data %>%
  summarize(r = cor(x, y))

## # A tibble: 1 × 1
##         r
##     <dbl>
## 1 -0.0630

Some more narrative can go here.

# Calculate the correlation here

Conclude with some more narrative, if needed.

Exercise 4

ggplot(datasaurus_dozen, aes(x = x, y = y, color = dataset))+
  geom_point()+
  facet_wrap(~ dataset, ncol = 3) +
  theme(legend.position = "none")

datasaurus_dozen %>%
  group_by(dataset) %>%
  summarize(r = cor(x, y)) 

## # A tibble: 13 × 2
##    dataset          r
##    <chr>        <dbl>
##  1 away       -0.0641
##  2 bullseye   -0.0686
##  3 circle     -0.0683
##  4 dino       -0.0645
##  5 dots       -0.0603
##  6 h_lines    -0.0617
##  7 high_lines -0.0685
##  8 slant_down -0.0690
##  9 slant_up   -0.0686
## 10 star       -0.0630
## 11 v_lines    -0.0694
## 12 wide_lines -0.0666
## 13 x_shape    -0.0656

The plots visualized the shape of each labeled.

Excercise 5

dino_data <- datasaurus_dozen %>%
  filter(dataset == "dino")
ggplot(data = dino_data, mapping = aes(x = x, y = y)) + 
  geom_point()

star_data <- datasaurus_dozen %>%
  filter(dataset == "star")
ggplot(data = star_data, mapping = aes(x = x, y = y)) +
  geom_point()

ggplot(datasaurus_dozen, aes(x = x, y = y, color = dataset))+
  geom_point()+
  facet_wrap(~ dataset, ncol = 3) +
  theme(legend.position = "none")