Chapter 3 ggplot2_Exercise5

3.1 Exercise 5-1

library(gcookbook)
library(tidyverse)
library(dplyr)
library(ggplot2)
ggplot(heightweight, aes(x=ageYear, y=heightIn, size=weightLb, color=sex))+geom_point()

ggplot(heightweight, aes(x=ageYear, y=heightIn, size=weightLb, color=sex))+geom_point(alpha=0.3)

ggplot(heightweight, aes(x=ageYear, y=heightIn, size=weightLb, color=sex))+geom_point(alpha=0.3) +
  labs(title="Height and weight of school children",
       subtitle="Height vs Weight",
       caption="Source: heightweight",
       x="Age (year)",
       y="Height (inches)",
       size="Weight(Lb)",
       color="Gender")

ggplot(heightweight, aes(x=ageYear, y=heightIn, size=weightLb, color=sex))+geom_point(alpha=0.3) +
  labs(title="Height and weight of school children",
       subtitle="Height vs Weight",
       caption="Source: heightweight",
       x="Age (year)",
       y="Height (inches)",
       size="Weight(Lb)",
       color="Gender") + theme_classic()

3.2 Exercise 5-2

ggplot(heightweight, aes(x=heightIn)) + geom_histogram()

ggplot(heightweight, aes(x=weightLb, fill=sex)) + geom_histogram()

ggplot(heightweight, aes(x=weightLb, fill=sex)) + 
  geom_histogram(alpha=0.4) + 
  scale_fill_manual(values=c("orange", "yellow"))

ggplot(heightweight, aes(x=weightLb, fill=sex)) + 
  geom_histogram(alpha=0.4) + 
  scale_fill_manual(values=c("orange", "yellow")) +
  labs(title = "A histogram of the weight of school children",
       subtitle = "By gender",
       x="WeightLb",
       y="Count",
       fill="Gender") + theme_minimal()

3.3 Exercise 5-3

ggplot(mpg, aes(x=hwy, fill=drv)) +
  geom_histogram(alpha=0.5) +
  facet_grid(vars(drv)) +
  labs(title= "Histogram using facet_grid()",
       subtitle= "Histogram of Highway Mile Per Gallon",
       caption= "Source: mpg") + theme_minimal()

3.4 Exercise 5-4

ggplot(midwest, aes(x = area, y = poptotal)) +
  geom_point(alpha=0.4, aes(size = popdensity, color = state)) + 
  geom_smooth(se=FALSE) +
  xlim(c(0, 0.1)) + 
  ylim(c(0, 500000)) +
  labs(title = "Scatterplot",
       subtitle = "Area Vs Population",
       x = "Area",
       y = "Population",
       caption = "midwest") +
  theme_classic()

## Warning: Removed 15 rows containing non-finite values (stat_smooth).

## Warning: Removed 15 rows containing missing values (geom_point).

3.5 Exercise 5-5

ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width, shape=Species, color=Species)) +
  geom_point(alpha=0.5, size=6) +
  theme_minimal() +
  labs(title = "Scatterplot",
       subtitle = "Sepal.Length Vs Sepal.Width",
       caption = "Source: iris")

3.6 Exercise 5-6

ggplot(heightweight, aes(x=heightIn, y=weightLb, color=sex)) +
  geom_point(alpha=0.5, size=3) +
  geom_smooth(se=FALSE, method="lm") +
  theme_classic() + 
  labs(title = "Scatterplot",
       subtitle = "Weight Vs Height",
       caption = "Source: heightweight")

3.7 Exercise 5-7

ggplot(mpg, aes(x=manufacturer, fill=class)) + 
  geom_bar(width = 0.5) +
  theme_minimal() +
  labs(title = "Barplot",
       subtitle = "Manufacturer across Vehicle Classes") +
  scale_fill_brewer(palette = "Spectral") +
  theme(axis.text.x = element_text(angle = 65))

3.8 Exercise 5-8

ggplot(cabbage_exp, aes(x=Date, y=Weight, fill=Cultivar)) +
  geom_bar(stat='identity', position="dodge") +
  geom_text(aes(label = Weight), colour = "white", size = 4, vjust = 1.5, position = position_dodge(.9)) +
  theme_minimal()