Breaking Bad

Breaking Bad is an American television drama series created by Vince Gilligan. It aired from 2008 to 2013 and starred Bryan Cranston as Walter White, a chemistry teacher turned methamphetamine producer, and Aaron Paul as his former student and business partner Jesse Pinkman.

The show received critical acclaim for its writing, acting, and cinematography, and is considered one of the greatest television series of all time.

Logo

Breaking Bad Logo

# Creating the dataset and saving it
viewership <- data.frame(
  Season = 1:5,
  Average_Viewership_Millions = c(1.23, 1.33, 1.52, 1.91, 6.04)
)

# Saving to CSV
write.csv(viewership, "data/breaking_bad_viewership.csv", row.names = FALSE)

## Summary Statistics


library(knitr)


viewership <- read.csv("data/breaking_bad_viewership.csv")

kable(viewership, caption = "Breaking Bad Average Viewership (in Millions)")

Breaking Bad Average Viewership (in Millions)
Season	Average_Viewership_Millions
1	1.23
2	1.33
3	1.52
4	1.91
5	6.04

# Show basic summary stats
summary(viewership$Average_Viewership_Millions)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   1.230   1.330   1.520   2.406   1.910   6.040

mean_viewers <- mean(viewership$Average_Viewership_Millions)
min_viewers <- min(viewership$Average_Viewership_Millions)
max_viewers <- max(viewership$Average_Viewership_Millions)

cat("Mean Viewership:", round(mean_viewers, 2), "million\n")

## Mean Viewership: 2.41 million

cat("Minimum Viewership:", round(min_viewers, 2), "million\n")

## Minimum Viewership: 1.23 million

cat("Maximum Viewership:", round(max_viewers, 2), "million\n")

## Maximum Viewership: 6.04 million

## Viewership Over Time


library(ggplot2)

#  plot
ggplot(viewership, aes(x = Season, y = Average_Viewership_Millions)) +
  geom_line(color = "darkgreen", size = 1.2) +
  geom_point(color = "blue", size = 3) +
  labs(
    title = "Breaking Bad Viewership Over Time",
    x = "Season",
    y = "Average Viewership (Millions)"
  ) +
  theme_minimal()

## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

## The Change in Viewership from Season to Season

# Calculating change from previous season
viewership$Change_Millions <- c(NA, diff(viewership$Average_Viewership_Millions))

# Showing the data
knitr::kable(viewership, caption = "Viewership Change Between Seasons")

Viewership Change Between Seasons
Season	Average_Viewership_Millions	Change_Millions
1	1.23	NA
2	1.33	0.10
3	1.52	0.19
4	1.91	0.39
5	6.04	4.13

# Plotting the change
ggplot(viewership[-1, ], aes(x = factor(Season), y = Change_Millions)) +
  geom_col(fill = "orange") +
  labs(
    title = "Change in Average Viewership Between Seasons",
    x = "Season",
    y = "Change in Viewership (Millions)"
  ) +
  theme_minimal()

Interpretation of Viewership Trends

The average viewership of Breaking Bad increased steadily across the first four seasons. Between Season 1 and Season 2, viewership increased by r round(viewership(viewrshio$Change_Millions[2], 2) million viewers. The growth continued into Season 3 and Season 4, with increases of r round(viewership(viewrshio$Change_Millions[3], 2) and r round(viewership(viewrshio$Change_Millions[4], 2) million, respectively.

The most significant jump occurred between Season 4 and Season 5, where viewership increased by r round(viewership(viewrshio$Change_Millions[5], 2) million, reaching an all-time high of r round(viewership(viewrshio$Change_Millions[5]) million viewers on average.

This surge may be attributed to growing critical acclaim and increased accessibility of earlier seasons via streaming platforms.

Conclusion

This short analysis of Breaking Bad viewership data shows a steady increase in average viewers over its five-season run. The final season saw a major spike of over 4 million additional viewers compared to Season 4, likely due to increased critical acclaim and streaming availability of earlier seasons. Visualizations and statistics highlight the show’s growing popularity and cultural impact.