Week 7: Apply it to your data 6

Question

The most popular season

Variation

    ggplot(data = data) +
    geom_bar(mapping = aes(x = SEASON))

Visualizing distributions

ggplot(data = data) +
    geom_histogram(mapping = aes(x = rank(SEASON)))

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

data %>% count(SEASON)

## # A tibble: 4 × 2
##   SEASON     n
##    <dbl> <int>
## 1      1   462
## 2      2     5
## 3      3   394
## 4      4    21

Covariation

ggplot(data = data, mapping = aes(x = SEASON, y = HOST)) +
  geom_boxplot()

## Warning: Continuous x aesthetic
## ℹ did you forget `aes(group = ...)`?

A categorical and continuous variable

ggplot(data = data, mapping = aes(x = SEASON, y = HOST_FACTOR)) +
  geom_boxplot()

ggplot(data = data, mapping = aes(x = SEASON, y = SMTDATE)) +
  geom_boxplot()

## Warning: Continuous x aesthetic
## ℹ did you forget `aes(group = ...)`?

## Warning: Removed 87 rows containing non-finite outside the scale range
## (`stat_boxplot()`).

Patterns and models

library(modelr)
    ggplot(data = data, aes(SEASON, CAMPS)) +
    geom_boxplot()

## Warning: Continuous x aesthetic
## ℹ did you forget `aes(group = ...)`?