Data Visualization using R (Assignment 3)

Formaldehyde

data(Formaldehyde)

plot(Formaldehyde,
     main = "Relation between Concentration and Rate of Reaction",
     xlab = "Carbohydrate (carb)",
     ylab = "Optical Density (optden)",
     col = "blue",
     pch = 16)

model_f <- lm(optden ~ carb, data = Formaldehyde)
abline(model_f, col = "red", lwd = 2)

data(CO2)

plot(CO2$conc, CO2$uptake,
     main = "CO2 Uptake vs Concentration",
     xlab = "Concentration",
     ylab = "Uptake",
     col = "blue",
     pch = 16)

model_co2 <- lm(uptake ~ conc, data = CO2)
abline(model_co2, col = "red", lwd = 2)

library(ggplot2)

ggplot(CO2, aes(x = conc, y = uptake)) +
  geom_point(color = "blue") +
  geom_smooth(method = "lm", color = "red", se = FALSE) +
  labs(title = "CO2 Uptake vs Concentration (GGPlot)")

## `geom_smooth()` using formula = 'y ~ x'

data(HairEyeColor)

hair_counts <- margin.table(HairEyeColor, 1)

barplot(hair_counts,
        main = "Distribution of Hair Color",
        xlab = "Hair Color",
        ylab = "Count",
        col = rainbow(length(hair_counts)))

hec_df <- as.data.frame(HairEyeColor)

ggplot(hec_df, aes(x = Hair, y = Freq, fill = Eye)) +
  geom_bar(stat = "identity", position = "dodge") +
  labs(title = "Hair Color vs Eye Color Distribution")