data(iris)
sepal_width <- iris$Sepal.Width
mean_sw <- mean(sepal_width)
var_sw <- var(sepal_width)
sd_sw <- sd(sepal_width)
data.frame(
Mean = mean_sw,
Variance = var_sw,
Std_Deviation = sd_sw
)
## Mean Variance Std_Deviation
## 1 3.057333 0.1899794 0.4358663
library(ggplot2)
ggplot(
data=iris,
mapping = aes(
x=Petal.Length,
y=Petal.Width,
color = Species)
)+
geom_point(size=2)+
labs(
title = "scatter plot of pedal length vs pedal width",
x="pedal length",
y="pedal width",
color="Species")+
theme_minimal()
# Bai 2:
write.csv(iris, "iris.csv", row.names = FALSE)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
total_by_species <- iris %>%
group_by(Species) %>%
summarise(
total_sepal_length = sum(Sepal.Length),
total_sepal_width = sum(Sepal.Width)
)
write.csv(total_by_species, "total_by_species.csv", row.names = FALSE)