Question 1

There are 150 observations and 5 variables in the dataset (iris).

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
## ✔ lubridate 1.9.3     ✔ tibble    3.2.1
## ✔ purrr     1.0.2     ✔ tidyr     1.3.1
## ── 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
data(iris)
class(iris)
## [1] "data.frame"

Question 2

There are 56 observations and 5 variables in the dataset (iris1).

iris1 <- iris%>%
  filter(Species %in% c("virginica","versicolor"), Sepal.Length > 6.0, Sepal.Width > 2.5)

Question 3

There are 56 observations and 3 variables in the dataset (iris2).

iris2 <- iris1%>%
  select("Species","Sepal.Length","Sepal.Width")

Question 4

iris3 <- iris2%>%
  arrange(by=Sepal.Length)
head(iris3)
##      Species Sepal.Length Sepal.Width
## 1 versicolor          6.1         2.9
## 2 versicolor          6.1         2.8
## 3 versicolor          6.1         2.8
## 4 versicolor          6.1         3.0
## 5  virginica          6.1         3.0
## 6  virginica          6.1         2.6

Question 5

iris4 <- iris3%>%
  mutate(Sepal.Area=Sepal.Length*Sepal.Width)

Question 6

iris5 <- iris4%>%
  summarize(Avg.Sepal.Length=mean(Sepal.Length),Avg.Sepal.Width=mean(Sepal.Width),Sample.Size=n())
print(iris5)
##   Avg.Sepal.Length Avg.Sepal.Width Sample.Size
## 1         6.698214        3.041071          56

Question 7

iris6 <- iris4%>%
  group_by(Species) %>%
  summarize(Avg.Sepal.Length=mean(Sepal.Length),Avg.Sepal.Width=mean(Sepal.Width),Sample.Size=n())
print(iris6)
## # A tibble: 2 × 4
##   Species    Avg.Sepal.Length Avg.Sepal.Width Sample.Size
##   <fct>                 <dbl>           <dbl>       <int>
## 1 versicolor             6.48            2.99          17
## 2 virginica              6.79            3.06          39

Question 8

irisFinal<- iris%>%
  filter(Species %in% c("virginica","versicolor"), Sepal.Length > 6.0, Sepal.Width > 2.5)%>% #iris1
  select("Species","Sepal.Length","Sepal.Width")%>% #iris2
  arrange(by=Sepal.Length)%>% #iris3
  mutate(Sepal.Area=Sepal.Length*Sepal.Width)%>% #iris4
  group_by(Species) %>% #iris6
  summarize(Avg.Sepal.Length=mean(Sepal.Length),Avg.Sepal.Width=mean(Sepal.Width),Sample.Size=n()) #iris6
print(irisFinal)
## # A tibble: 2 × 4
##   Species    Avg.Sepal.Length Avg.Sepal.Width Sample.Size
##   <fct>                 <dbl>           <dbl>       <int>
## 1 versicolor             6.48            2.99          17
## 2 virginica              6.79            3.06          39

Question 9

iris%>%
  pivot_longer(col=Sepal.Length:Petal.Width, names_to="Measure",values_to="Value")
## # A tibble: 600 × 3
##    Species Measure      Value
##    <fct>   <chr>        <dbl>
##  1 setosa  Sepal.Length   5.1
##  2 setosa  Sepal.Width    3.5
##  3 setosa  Petal.Length   1.4
##  4 setosa  Petal.Width    0.2
##  5 setosa  Sepal.Length   4.9
##  6 setosa  Sepal.Width    3  
##  7 setosa  Petal.Length   1.4
##  8 setosa  Petal.Width    0.2
##  9 setosa  Sepal.Length   4.7
## 10 setosa  Sepal.Width    3.2
## # ℹ 590 more rows