library(ggplot2)
library(gganimate)
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
data <- read.csv("Cal_Fire_Perimeters.csv")
data
library(gapminder)

p <- ggplot(
  data, 
  aes(x = YEAR_, y=REPORT_AC, size = GIS_ACRES, colour = AGENCY)
  ) +
  geom_point(show.legend = FALSE, alpha = 0.7) +
  scale_color_viridis_d() +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  labs(x = "GDP per capita", y = "Life expectancy")
p
## Warning: Removed 7968 rows containing missing values (geom_point).

p + transition_time(YEAR_) +
  labs(title = "Year: {frame_time}")
## Warning: Removed 213 rows containing missing values (geom_point).

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p <- ggplot(
  gapminder, 
  aes(x = gdpPercap, y=lifeExp, size = pop, colour = country)
  ) +
  geom_point(show.legend = FALSE, alpha = 0.7) +
  scale_color_viridis_d() +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  labs(x = "GDP per capita", y = "Life expectancy")

p + transition_time(year) +
  labs(title = "Year: {frame_time}")