December 9, 2019

Philadelphia Parking Tickets: a tidyTuesday

Philadelphia Map

Use ggmap for the base layer.

library(ggmap); library(osmdata); library(tidyverse)
PHI <- get_map(getbb("Philadelphia, PA"), maptype = "stamen", zoom=12)

Get the Tickets Data

TidyTuesday covers 1.26 million parking tickets in Philadelphia.

tickets <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-12-03/tickets.csv")

## Parsed with column specification:
## cols(
##   violation_desc = col_character(),
##   issue_datetime = col_datetime(format = ""),
##   fine = col_double(),
##   issuing_agency = col_character(),
##   lat = col_double(),
##   lon = col_double(),
##   zip_code = col_double()
## )

Two Lines of Code Left

library(lubridate); library(ggthemes)
tickets <- tickets %>% mutate(Day = wday(issue_datetime, label=TRUE)) # use lubridate to extract the day of the month.
Philly.Tix <- ggmap(PHI) + stat_density2d(data=tickets, aes(x=lon, y=lat, fill=..level.., alpha=..level..), bins=30, size=0.01, geom="polygon", contour=TRUE) + scale_fill_viridis_c() + guides(alpha=FALSE) + labs(title="Philly Tickets", fill="Ticket Frequency") + theme_map() + theme(legend.position = "right")
Philly.Tix

An Animation

library(gganimate) 
Philly.Tix <- ggmap(PHI) + stat_density2d(data=tickets, aes(x=lon, y=lat, fill=stat(level), alpha=stat(level)), bins=30, size=0.01, geom="polygon", contour=TRUE) + geom_point(y=39.8942978,x=-75.1945002, col="pink", size=4) + scale_fill_viridis_c() + guides(alpha=FALSE) + labs(title="Philly Tickets", fill="Ticket Frequency") + theme_map() + theme(legend.position = "right") 
Philly.Tix + labs(subtitle = "{closest_state}") + transition_states(Day, transition_length = 3, state_length = 5, wrap = TRUE)

Facets

Philly.Tix <- ggmap(PHI) + stat_density2d(data=tickets, aes(x=lon, y=lat, fill=stat(nlevel), alpha=stat(nlevel), group=issuing_agency), bins=30, size=0.01, geom="polygon", contour=TRUE) + scale_fill_viridis_c() + geom_point(y=39.8942978,x=-75.1945002, col="pink") + guides(alpha=FALSE) + labs(title="Philly Tickets", fill="Ticket Frequency") + theme_map() + theme(legend.position = "right") + facet_wrap(vars(issuing_agency))
Philly.Tix + labs(subtitle = "{closest_state}") + transition_states(Day, transition_length = 3, state_length = 5, wrap = TRUE)

A Dot Plot

Philly.Tix.Dots <- ggmap(PHI) + geom_point(data=tickets, aes(x=lon, y=lat, color=issuing_agency, size=fine/100000), alpha=0.02) + scale_fill_viridis_d() + guides(alpha=FALSE) + guides(colour = guide_legend(override.aes = list(alpha = 1))) + labs(title="Philly Tickets", color="Issuer", size="Fine Amount") + theme_map() + theme(legend.position = "right") 
# + labs(title = "{closest_state}") + transition_states(Day, transition_length = 3, state_length = 1, wrap = TRUE)
Philly.Tix.Dots + facet_wrap(vars(Day))

## Warning: Removed 1161 rows containing missing values (geom_point).