install.packages("tidyverse")
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.5'
## (as 'lib' is unspecified)
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.2.0 ✔ readr 2.2.0
## ✔ forcats 1.0.1 ✔ stringr 1.6.0
## ✔ ggplot2 4.0.2 ✔ tibble 3.3.1
## ✔ lubridate 1.9.5 ✔ tidyr 1.3.2
## ✔ purrr 1.2.1
## ── 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
ggplot(data = BOD,
mapping = aes(x = Time,
y = demand)) + # creates the graph but does not have points
geom_point(size = 5) + # geom adds points, editing point size
geom_line(color = "red") #adding a line and changning color
ggplot(BOD, aes(Time, demand))+
geom_point(size = 3)+
geom_line(color = "red")
CO2 %>%
ggplot(aes(conc, uptake,
color = Treatment))+
geom_point(size = 3, alpha = 0.5)+
geom_smooth(method = lm, se = F)+
facet_wrap (~Type) +
labs (title = "Concentration of CO2")+
theme_bw()
## `geom_smooth()` using formula = 'y ~ x'
CO2 %>%
ggplot(aes(Treatment, uptake))+
geom_boxplot()+
geom_point(alpha = 0.5,
aes(size= conc,
color = Plant)) +
facet_wrap(~Type)+
coord_flip()+
theme_bw()+
labs(title = "Chilled vs Non-chilled")
(alpha) is how transparent something is
head(mpg)
## # A tibble: 6 × 11
## manufacturer model displ year cyl trans drv cty hwy fl class
## <chr> <chr> <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
## 1 audi a4 1.8 1999 4 auto(l5) f 18 29 p compa…
## 2 audi a4 1.8 1999 4 manual(m5) f 21 29 p compa…
## 3 audi a4 2 2008 4 manual(m6) f 20 31 p compa…
## 4 audi a4 2 2008 4 auto(av) f 21 30 p compa…
## 5 audi a4 2.8 1999 6 auto(l5) f 16 26 p compa…
## 6 audi a4 2.8 1999 6 manual(m5) f 18 26 p compa…
mpg %>%
filter(cty<25) %>%
ggplot(aes(displ, cty))+
geom_point(aes(color = drv,
size = trans),
alpha = 0.5) +
geom_smooth(method = lm) +
facet_wrap(~year, nrow = 1)+
labs(x = "Engine size",
y = "MPG in the city",
title = "Fuel efficiency")+
theme_bw()
## Warning: Using size for a discrete variable is not advised.
## `geom_smooth()` using formula = 'y ~ x'