Time Series

geom_line() in ggplot2 is used to create a line plot by connecting data points with a continuous line, which is ideal for visualizing trends over time. It is particularly useful for time series data because it clearly shows how a variable changes across ordered time intervals, allowing for easy identification of patterns and trends.

#| include: false
library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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✔ forcats   1.0.0     ✔ stringr   1.5.1
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✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.4     
── 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

library(RandomData)

?constructors_stats

# Calculate total wins per year for Ferrari
ferrari_wins <- constructors_stats |>
  filter(constructor == "Ferrari") |>
  group_by(year) |> 
  summarize(total_wins = sum(max(constructor_wins)))

ggplot(ferrari_wins, aes(x = year, y = total_wins)) +
  geom_line(color = "red", linewidth = 1.2) +  # Creates a red line plot
  labs(title = "Ferrari Wins 1958 to 2024 (Before the Summer Break)", 
       x = "Year", 
       y = "Wins") +
  theme_classic()

aes(x = year, y = total_wins):
- x = year: Puts the years on the x-axis.
- y = total_wins: Puts the total number of wins on the y-axis.
geom_line(color = "red", linewidth = 1.2):
- geom_line(): Creates a line plot instead of points.
- color = "red": Adds a color to the line
- linewidth = 1.2: Makes the line slightly thicker for better visibility.