streeteasy-gganimate.R

library(tidyverse)
library(gganimate)
library(gifski)
library(png)
library(scales)

# import
inventory = read.csv('https://raw.githubusercontent.com/erikgregorywebb/datasets/master/rentalInventory_All.csv', stringsAsFactors = F)
inventory = inventory %>% gather('Month', 'Inventory', -areaName, -Borough, -areaType)

# clean
inventory$Year = substr(sub('X', '', inventory$Month), 1, 4)
inventory$Month = substr(sub('X', '', inventory$Month), 6, 8)
inventory$Date = as.Date(paste(inventory$Year, inventory$Month, '01', sep = '-'))

# 1. Inventory by Borough Over Time
p1 = inventory %>%
  filter(areaType == 'borough') %>% 
  filter(Borough != 'Staten Island') %>%
  ggplot(aes(Date, Inventory, group = areaName)) + 
  geom_line(color='steelblue', size = 1) + 
  geom_segment(aes(xend = as.Date('2019-01-01', format = '%Y-%m-%d'), yend = Inventory), linetype = 2, colour = 'grey') + 
  geom_point(color='steelblue', size = 1) + 
  geom_text(aes(x = as.Date('2019-01-01', format = '%Y-%m-%d'), label = areaName), hjust = 0, size = 6) + 
  scale_y_continuous(label = comma) + 
  scale_x_date(limits = c(as.Date('2010-01-01', format = '%Y-%m-%d'), as.Date('2019-05-01', format = '%Y-%m-%d'))) + 
  transition_reveal(Date) + 
  coord_cartesian(clip = 'off') + 
  labs(title = 'NYC Rental Inventory by Borough', 
       subtitle = 'Source: StreetEasy, 2010-18', 
       y = 'Avaliable Units') + 
  theme_minimal() +
  theme(text = element_text(size = 18)) + 
  theme(plot.title = element_text(size = 24)) +
  theme(plot.margin = margin(5.5, 50, 5.5, 5.5))

anim_save("p1.gif", p1, width = 1000, height = 650)

# 2. Average Monthly Inventory by Borough
p2 = inventory %>% 
  filter(areaType == 'borough') %>%
  filter(Borough != 'Staten Island') %>%
  group_by(Borough, Month) %>%
  summarise(avgInventory = mean(Inventory)) %>%
  mutate(Month = as.numeric(Month)) %>%
  ggplot(aes(Month, avgInventory, group = Borough)) + 
  geom_line(color='steelblue', size = 1) + 
  geom_segment(aes(xend = 12, yend = avgInventory), linetype = 2, colour = 'grey') + 
  geom_point(color='steelblue', size = 1) + 
  geom_text(aes(x = 12, label = Borough), hjust = 0, size = 6) + 
  scale_y_continuous(label = comma) + 
  scale_x_discrete(limits=1:12, labels = month.abb) + 
  transition_reveal(Month) + 
  coord_cartesian(clip = 'off') + 
  labs(title = 'Average NYC Monthly Inventory by Borough', 
       subtitle = 'Source: StreetEasy, 2010-18', 
       y = 'Avaliable Units') + 
  theme_minimal() +
  theme(text = element_text(size = 18)) + 
  theme(plot.title = element_text(size = 24)) +
  theme(plot.margin = margin(5.5, 50, 5.5, 5.5))

anim_save("p2.gif", p2, width = 1000, height = 650)

# 3. Rental Inventory in Brooklyn's Neighborhoods
p3 = inventory %>%
  filter(areaType == 'neighborhood',
         Borough == 'Brooklyn') %>%
  ggplot(aes(Date, Inventory, group = areaName)) + 
  geom_line(color='steelblue', size = 1) + 
  geom_point(color='steelblue', size = 1) + 
  facet_wrap(~areaName) + 
  theme(axis.text.x=element_blank(), axis.text.y=element_blank(), axis.ticks=element_blank()) + 
  transition_reveal(Date) + 
  coord_cartesian(clip = 'off') + 
  labs(title = 'Rental Inventory in Brooklyn Neighborhoods', 
       subtitle = 'Source: StreetEasy, 2010-18', 
       y = 'Avaliable Units') + 
  theme_minimal() +
  theme(text = element_text(size = 18)) + 
  theme(plot.title = element_text(size = 24)) +
  theme(plot.margin = margin(5.5, 50, 5.5, 5.5))
  
anim_save("p3.gif", p3, width = 1000, height = 650)

# Note: animate(p1, fps = 12, renderer = gifski_renderer(loop = TRUE))