Siyu_LabHW_Animated

Add the data of New Jersey (including a new annotation) to the same plot so that the graph shows evolution of college tuition in New York and New Jersey in the same plot.

read_csv("D:/Mysoftware/DefaultWD-R/dataset/us_avg_tuition.csv") -> tuition_data

tuition_data <- tuition_data %>% 
  pivot_longer(cols = 2:13, names_to = "year", values_to = "tuition") %>%
  extract(year, into = "year", "^(....)") %>%
  mutate(tuition = parse_number(tuition)) %>%
  mutate(year = as.numeric(year))

nj_ny_data <- tuition_data %>% 
  filter(State == "New Jersey" |State == "New York")

ggplot(nj_ny_data, aes(x = year, y = tuition, group = State, color = State)) + 
  geom_line() + geom_point() + 
  annotate("text", label = "New Jersey", x = 2004.8, y = 10400) +
  annotate("text", label = "New York", x = 2004.5, y = 6500) +
  labs(title = "Evolution of College Tuition in New York and New Jersey",
       x = "Year",
       y = "Average Tution($)") +
  transition_reveal(year)

Try to reproduce the following graph:

ggplot(tuition_data, aes(x = tuition, y = State, color = State)) + 
  geom_bar(stat = "identity", show.legend = F) +
  transition_time(year) +
  labs(title = 'Year: {round(frame_time)}', 
       x = "Tuition(in USD)",
       y = "States") +
  theme(plot.title = element_text(hjust = 0.5)) 

Try to reproduce the following graph with the diamonds data set

diamonds

## # A tibble: 53,940 × 10
##    carat cut       color clarity depth table price     x     y     z
##    <dbl> <ord>     <ord> <ord>   <dbl> <dbl> <int> <dbl> <dbl> <dbl>
##  1  0.23 Ideal     E     SI2      61.5    55   326  3.95  3.98  2.43
##  2  0.21 Premium   E     SI1      59.8    61   326  3.89  3.84  2.31
##  3  0.23 Good      E     VS1      56.9    65   327  4.05  4.07  2.31
##  4  0.29 Premium   I     VS2      62.4    58   334  4.2   4.23  2.63
##  5  0.31 Good      J     SI2      63.3    58   335  4.34  4.35  2.75
##  6  0.24 Very Good J     VVS2     62.8    57   336  3.94  3.96  2.48
##  7  0.24 Very Good I     VVS1     62.3    57   336  3.95  3.98  2.47
##  8  0.26 Very Good H     SI1      61.9    55   337  4.07  4.11  2.53
##  9  0.22 Fair      E     VS2      65.1    61   337  3.87  3.78  2.49
## 10  0.23 Very Good H     VS1      59.4    61   338  4     4.05  2.39
## # ℹ 53,930 more rows

ggplot(diamonds, aes(x = carat, y = price, color = color)) +
  geom_point() +
  geom_smooth(method = "loess", color = "blue") +
  labs(title = 'Cut Quality:{closest_state}',
       x = "Carat",
       y = "Price(USD)") +
  transition_states(cut) +
  theme(plot.title = element_text(hjust = 0.5))