Variation

Visualizing distributions

diamonds %>%
    ggplot(aes(x=cut)) +
    geom_bar()

diamonds %>%
    ggplot(mapping = aes(x = carat)) +
    geom_histogram(binwidth = .5)

diamonds %>%
    
    filter(carat < 3) %>%
    
    ggplot(aes(x = carat)) + 
    geom_histogram(binwidth = 0.5)

diamonds %>%
    ggplot(aes(x= carat, color = cut)) +
    geom_freqpoly()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

### Typical values

diamonds %>%
    #filter out diamonds > 3 carat
    filter(carat < 3) %>%
    #plot
    ggplot(aes(x=carat)) +
    geom_histogram(binwidth = 0.01)

faithful %>%
    ggplot(aes(eruptions)) +
    geom_histogram(binwidth = 0.25)

Unusual values

diamonds %>%
    ggplot(aes(y)) +
    geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

diamonds %>%
    ggplot(aes(y)) +
    geom_histogram() +
    coord_cartesian(ylim = c(0,50))
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

## Missing Values

diamonds %>% 
    
    #filter( y <3 | y > 20) %>%
    
    mutate(y =ifelse(y < 3 | y > 20, NA, y)) %>%
    #plot
    ggplot(aes(x = x, y = y)) +
    geom_point()
## Warning: Removed 9 rows containing missing values or values outside the scale range
## (`geom_point()`).

## Covariation

A categorical and continous variable

diamonds %>%
    
    ggplot(aes(x = cut, y = price)) +
    geom_boxplot()

### Two categorical

diamonds %>%
    count(color,cut) %>%
    
    ggplot(aes(x=color, y =cut, fill =n)) +
    geom_tile()

### Two continous variable

library(hexbin)
## Warning: package 'hexbin' was built under R version 4.4.3
diamonds %>%
    ggplot(aes(x = carat, y = price)) +
    geom_hex()

diamonds %>%
    ggplot(aes(x = carat, y = price)) +
    geom_boxplot(aes(group = cut_width(carat, 0.1)))

## Patterns and models

library(modelr)
mod <- lm(log(price) ~ log(carat), data = diamonds)

diamonds4 <- diamonds %>%
    modelr::add_residuals(mod) %>%
    mutate(resid = exp(resid))


diamonds4 %>%
    ggplot(aes(carat, resid)) +
    geom_point()

diamonds4 %>%
    ggplot(aes(cut,resid))+
    geom_boxplot()