R For Data Science Cheat Sheet.pdf

Introduction to the Tidyverse chapter2.pdf

# Load the ggplot2 package as well
library(gapminder)
library(dplyr)
library(ggplot2)

# Create gapminder_1952
gapminder_1952 <- gapminder %>%filter(year==1952)

gapminder_1952 <- gapminder %>%
  filter(year == 1952)

# Change to put pop on the x-axis and gdpPercap on the y-axis
ggplot(gapminder_1952, aes(x = pop, y = gdpPercap)) +
  geom_point()

gapminder_1952 <- gapminder %>%
  filter(year == 1952)
# Create a scatter plot with pop on the x-axis and lifeExp on the y-axis
ggplot(gapminder_1952, aes(x=pop, y=lifeExp) )+
geom_point()

Log scales

library(gapminder)
library(dplyr)
library(ggplot2)

gapminder_1952 <- gapminder %>%
  filter(year == 1952)

# Change this plot to put the x-axis on a log scale
ggplot(gapminder_1952, aes(x = pop, y = lifeExp)) +
  geom_point()+
  scale_x_log10()

#Great! Notice that the y-axis goes from 1e3 (1000) to 1e4 (10,000) to 1e5 (100,000) in equal increments.

# Scatter plot comparing pop and gdpPercap, with both axes on a log scale
ggplot(gapminder_1952, aes(x=pop, y=gdpPercap))+
geom_point()+

scale_x_log10()+
scale_y_log10()