→ Titles

Q1.1 The code below builds a basic histogram for Rbnb apartment prices on the French Riviera. It shows only value under 300 euros. Add code to:

• add a title with ggtitle()
• change axis labels xlab() and ylab()
• change axis limits with xlim() and ylim()

# Libraries
library(ggplot2)

# Load dataset from github
data <- read.table("https://raw.githubusercontent.com/holtzy/data_to_viz/master/Example_dataset/1_OneNum.csv", header=TRUE)

# Make the histogram
data %>%
  filter( price<300 ) %>%
  ggplot( aes(x=price)) +
    geom_histogram() +
    ggtitle("Night price distribution of Airbnb appartements") +
    xlab("Night price") +
    ylab("Number of apartments") +
    xlim(0,400)

→ Chart components

All ggplot2 chart components can be changed using the theme() function. You can see a complete list of components in the official documentation.

Note: components are changed using different functions: element_text(), element_line() for lines and so on..

Q1.2 Reproduce the previous histogram and change:

• plot title size and color with plot.title
• X axis title size and color with axis.title.x
• Grid appearance with panel.grid.major

# Make the histogram
data %>%
  filter( price<300 ) %>%
  ggplot( aes(x=price)) +
    geom_histogram() +
    ggtitle("Night price distribution of Airbnb appartements") +
    xlab("Night price") +
    ylab("Number of apartments") +
    xlim(0,400) +
    theme(
      plot.title = element_text(size=13, color="orange"),
      axis.title.x = element_text(size=13, color="purple"),
      panel.grid.major = element_line(colour = "red")
    )

→ Themes

Q1.3 ggplot2 offers a set of pre-built themes. Try the followings to see which one you like the most:

• theme_bw()
• theme_dark()
• theme_minimal()
• theme_classic()

See a complete list here.

# Load dataset from github
data <- read.table("https://raw.githubusercontent.com/holtzy/data_to_viz/master/Example_dataset/1_OneNum.csv", header=TRUE)

# Make the histogram
data %>%
  filter( price<300 ) %>%
  ggplot( aes(x=price)) +
    geom_histogram(fill="#69b3a2", color="#e9ecef", alpha=0.9) +
    ggtitle("Night price distribution of Airbnb appartements") +
    theme_classic()

Q1.4 The hrbrthemes package provides my favourite style. Install the package, load it, and apply the theme_ipsum(). Documentation is here.

# Libraries
library(tidyverse)
library(hrbrthemes)
library(viridis)

# Load dataset from github
data <- read.table("https://raw.githubusercontent.com/holtzy/data_to_viz/master/Example_dataset/1_OneNum.csv", header=TRUE)

# Make the histogram
data %>%
  filter( price<300 ) %>%
  ggplot( aes(x=price)) +
    stat_bin(breaks=seq(0,300,10), fill="#69b3a2", color="#e9ecef", alpha=0.9) +
    ggtitle("Night price distribution of Airbnb appartements") +
    theme_ipsum()