Visualization of BIKETOWN data for CascadiaRConference 2018
Code in BikeTown_cRaggy_visualization_KWS.Rmd
HTML of knitted code and output in BikeTown_cRaggy_visualization_KWS.html
# Packages
library(tidyverse)## -- Attaching packages ------------------------------------------------------------------------------- tidyverse 1.2.1 --
## v ggplot2 2.2.1 v purrr 0.2.4
## v tibble 1.4.2 v dplyr 0.7.4
## v tidyr 0.8.0 v stringr 1.3.0
## v readr 1.1.1 v forcats 0.3.0
## -- Conflicts ---------------------------------------------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(lubridate)##
## Attaching package: 'lubridate'
## The following object is masked from 'package:base':
##
## date
library(ggmap)## Google Maps API Terms of Service: http://developers.google.com/maps/terms.
## Please cite ggmap if you use it: see citation("ggmap") for details.
library(ggthemes)
library(ggrepel)
library(extrafont)## Registering fonts with R
# Fonts for export
# loadfonts(device = "win")
# loadfonts()
# Color choices from BIKETOWN website
bikeorange <- "#FC4C02"
darkgray <- "#393737"
medgray <- "#434345"
lightgray <- "#75787B"
medbkgd <- "#D4D2D3"
lightbkgd <- "#E4E2E3"Using all of the quarterly csv files
Data from: https://s3.amazonaws.com/biketown-tripdata-public/BiketownPublicTripData201804.zip
filelist <- list.files("PublicTripData/Quarterly") # data as downloaded
raw_bike <- data.frame()
for(f in filelist) {
temp_bike <- read_csv(paste0("PublicTripData/Quarterly/", f)) %>%
mutate(Duration = as.difftime(Duration)) #Necessary to fix a join issue with different csv's
raw_bike <- raw_bike %>% bind_rows(temp_bike)
}## Parsed with column specification:
## cols(
## RouteID = col_integer(),
## PaymentPlan = col_character(),
## StartHub = col_character(),
## StartLatitude = col_double(),
## StartLongitude = col_double(),
## StartDate = col_character(),
## StartTime = col_time(format = ""),
## EndHub = col_character(),
## EndLatitude = col_double(),
## EndLongitude = col_double(),
## EndDate = col_character(),
## EndTime = col_time(format = ""),
## TripType = col_character(),
## BikeID = col_integer(),
## BikeName = col_character(),
## Distance_Miles = col_double(),
## Duration = col_time(format = ""),
## RentalAccessPath = col_character(),
## MultipleRental = col_logical()
## )
## Warning in rbind(names(probs), probs_f): number of columns of result is not
## a multiple of vector length (arg 1)
## Warning: 33 parsing failures.
## row # A tibble: 5 x 5 col row col expected actual file expected <int> <chr> <chr> <chr> <chr> actual 1 2303 Duration valid date 46:46:51 'PublicTripData/Quarterly/2016_07_09~ file 2 4176 Duration valid date 26:13:31 'PublicTripData/Quarterly/2016_07_09~ row 3 7502 Duration valid date 28:54:41 'PublicTripData/Quarterly/2016_07_09~ col 4 8463 Duration valid date 24:22:19 'PublicTripData/Quarterly/2016_07_09~ expected 5 8532 Duration valid date 24:08:50 'PublicTripData/Quarterly/2016_07_09~
## ... ................. ... .......................................................................... ........ .......................................................................... ...... .......................................................................... .... .......................................................................... ... .......................................................................... ... .......................................................................... ........ ..........................................................................
## See problems(...) for more details.
## Parsed with column specification:
## cols(
## RouteID = col_integer(),
## PaymentPlan = col_character(),
## StartHub = col_character(),
## StartLatitude = col_double(),
## StartLongitude = col_double(),
## StartDate = col_character(),
## StartTime = col_time(format = ""),
## EndHub = col_character(),
## EndLatitude = col_double(),
## EndLongitude = col_double(),
## EndDate = col_character(),
## EndTime = col_time(format = ""),
## TripType = col_character(),
## BikeID = col_integer(),
## BikeName = col_character(),
## Distance_Miles = col_double(),
## Duration = col_time(format = ""),
## RentalAccessPath = col_character(),
## MultipleRental = col_logical()
## )
## Warning in rbind(names(probs), probs_f): number of columns of result is not
## a multiple of vector length (arg 1)
## Warning: 9 parsing failures.
## row # A tibble: 5 x 5 col row col expected actual file expected <int> <chr> <chr> <chr> <chr> actual 1 8336 Duration valid date 43:30:19 'PublicTripData/Quarterly/2016_10_12~ file 2 18926 Duration valid date 25:10:47 'PublicTripData/Quarterly/2016_10_12~ row 3 19349 Duration valid date 24:56:46 'PublicTripData/Quarterly/2016_10_12~ col 4 26300 Duration valid date 27:41:04 'PublicTripData/Quarterly/2016_10_12~ expected 5 39287 Duration valid date 30:54:43 'PublicTripData/Quarterly/2016_10_12~
## ... ................. ... .......................................................................... ........ .......................................................................... ...... .......................................................................... .... .......................................................................... ... .......................................................................... ... .......................................................................... ........ ..........................................................................
## See problems(...) for more details.
## Parsed with column specification:
## cols(
## RouteID = col_integer(),
## PaymentPlan = col_character(),
## StartHub = col_character(),
## StartLatitude = col_double(),
## StartLongitude = col_double(),
## StartDate = col_character(),
## StartTime = col_time(format = ""),
## EndHub = col_character(),
## EndLatitude = col_double(),
## EndLongitude = col_double(),
## EndDate = col_character(),
## EndTime = col_time(format = ""),
## TripType = col_character(),
## BikeID = col_integer(),
## BikeName = col_character(),
## Distance_Miles = col_double(),
## Duration = col_time(format = ""),
## RentalAccessPath = col_character(),
## MultipleRental = col_logical()
## )
## Warning in rbind(names(probs), probs_f): number of columns of result is not
## a multiple of vector length (arg 1)
## Warning: 14 parsing failures.
## row # A tibble: 5 x 5 col row col expected actual file expected <int> <chr> <chr> <chr> <chr> actual 1 1687 Duration valid date 48:18:45 'PublicTripData/Quarterly/2017_01_03~ file 2 1757 Duration valid date 48:04:21 'PublicTripData/Quarterly/2017_01_03~ row 3 1785 Duration valid date 48:00:12 'PublicTripData/Quarterly/2017_01_03~ col 4 1906 Duration valid date 29:02:25 'PublicTripData/Quarterly/2017_01_03~ expected 5 2177 Duration valid date 48:06:08 'PublicTripData/Quarterly/2017_01_03~
## ... ................. ... .......................................................................... ........ .......................................................................... ...... .......................................................................... .... .......................................................................... ... .......................................................................... ... .......................................................................... ........ ..........................................................................
## See problems(...) for more details.
## Parsed with column specification:
## cols(
## RouteID = col_integer(),
## PaymentPlan = col_character(),
## StartHub = col_character(),
## StartLatitude = col_double(),
## StartLongitude = col_double(),
## StartDate = col_character(),
## StartTime = col_time(format = ""),
## EndHub = col_character(),
## EndLatitude = col_double(),
## EndLongitude = col_double(),
## EndDate = col_character(),
## EndTime = col_time(format = ""),
## TripType = col_character(),
## BikeID = col_integer(),
## BikeName = col_character(),
## Distance_Miles = col_double(),
## Duration = col_character(),
## RentalAccessPath = col_character(),
## MultipleRental = col_logical()
## )
## Parsed with column specification:
## cols(
## RouteID = col_integer(),
## PaymentPlan = col_character(),
## StartHub = col_character(),
## StartLatitude = col_double(),
## StartLongitude = col_double(),
## StartDate = col_character(),
## StartTime = col_time(format = ""),
## EndHub = col_character(),
## EndLatitude = col_double(),
## EndLongitude = col_double(),
## EndDate = col_character(),
## EndTime = col_time(format = ""),
## TripType = col_character(),
## BikeID = col_integer(),
## BikeName = col_character(),
## Distance_Miles = col_double(),
## Duration = col_time(format = ""),
## RentalAccessPath = col_character(),
## MultipleRental = col_logical()
## )
## Warning in rbind(names(probs), probs_f): number of columns of result is not
## a multiple of vector length (arg 1)
## Warning: 37 parsing failures.
## row # A tibble: 5 x 5 col row col expected actual file expected <int> <chr> <chr> <chr> <chr> actual 1 3382 Duration valid date 38:41:55 'PublicTripData/Quarterly/2017~ file 2 3595 Duration valid date 65:35:58 'PublicTripData/Quarterly/2017~ row 3 4216 Duration "time like " 547955:05:27 'PublicTripData/Quarterly/2017~ col 4 8524 Duration valid date 34:04:29 'PublicTripData/Quarterly/2017~ expected 5 16945 Duration valid date 26:40:17 'PublicTripData/Quarterly/2017~
## ... ................. ... .......................................................................... ........ .......................................................................... ...... .......................................................................... .... .......................................................................... ... .......................................................................... ... .......................................................................... ........ ..........................................................................
## See problems(...) for more details.
## Parsed with column specification:
## cols(
## RouteID = col_integer(),
## PaymentPlan = col_character(),
## StartHub = col_character(),
## StartLatitude = col_double(),
## StartLongitude = col_double(),
## StartDate = col_character(),
## StartTime = col_time(format = ""),
## EndHub = col_character(),
## EndLatitude = col_double(),
## EndLongitude = col_double(),
## EndDate = col_character(),
## EndTime = col_time(format = ""),
## TripType = col_character(),
## BikeID = col_integer(),
## BikeName = col_character(),
## Distance_Miles = col_double(),
## Duration = col_time(format = ""),
## RentalAccessPath = col_character(),
## MultipleRental = col_logical()
## )
## Warning in rbind(names(probs), probs_f): number of columns of result is not
## a multiple of vector length (arg 1)
## Warning: 10 parsing failures.
## row # A tibble: 5 x 5 col row col expected actual file expected <int> <chr> <chr> <chr> <chr> actual 1 989 Duration valid date 31:09:56 'PublicTripData/Quarterly/2017_10_12~ file 2 1318 Duration valid date 40:23:13 'PublicTripData/Quarterly/2017_10_12~ row 3 1438 Duration valid date 32:09:27 'PublicTripData/Quarterly/2017_10_12~ col 4 16832 Duration valid date 27:13:13 'PublicTripData/Quarterly/2017_10_12~ expected 5 18452 Duration valid date 48:16:35 'PublicTripData/Quarterly/2017_10_12~
## ... ................. ... .......................................................................... ........ .......................................................................... ...... .......................................................................... .... .......................................................................... ... .......................................................................... ... .......................................................................... ........ ..........................................................................
## See problems(...) for more details.
## Parsed with column specification:
## cols(
## RouteID = col_integer(),
## PaymentPlan = col_character(),
## StartHub = col_character(),
## StartLatitude = col_double(),
## StartLongitude = col_double(),
## StartDate = col_character(),
## StartTime = col_time(format = ""),
## EndHub = col_character(),
## EndLatitude = col_double(),
## EndLongitude = col_double(),
## EndDate = col_character(),
## EndTime = col_time(format = ""),
## TripType = col_character(),
## BikeID = col_integer(),
## BikeName = col_character(),
## Distance_Miles = col_double(),
## Duration = col_time(format = ""),
## RentalAccessPath = col_character(),
## MultipleRental = col_logical()
## )
## Warning in rbind(names(probs), probs_f): number of columns of result is not
## a multiple of vector length (arg 1)
## Warning: 15 parsing failures.
## row # A tibble: 5 x 5 col row col expected actual file expected <int> <chr> <chr> <chr> <chr> actual 1 905 Duration valid date 27:29:18 'PublicTripData/Quarterly/2018_01_03~ file 2 11205 Duration valid date 40:06:36 'PublicTripData/Quarterly/2018_01_03~ row 3 11337 Duration valid date 40:26:06 'PublicTripData/Quarterly/2018_01_03~ col 4 14801 Duration valid date 31:46:02 'PublicTripData/Quarterly/2018_01_03~ expected 5 14927 Duration valid date 35:33:50 'PublicTripData/Quarterly/2018_01_03~
## ... ................. ... .......................................................................... ........ .......................................................................... ...... .......................................................................... .... .......................................................................... ... .......................................................................... ... .......................................................................... ........ ..........................................................................
## See problems(...) for more details.
bike_parsed <- raw_bike %>%
mutate(StartDate = mdy(StartDate)) %>%
mutate(start_wday = wday(StartDate, label = TRUE)) %>%
mutate(weekend = case_when(
str_detect(start_wday, "Sun|Sat") ~ "Weekend",
TRUE ~ "Weekday"))
summary(bike_parsed)## RouteID PaymentPlan StartHub StartLatitude
## Min. :1282087 Length:519500 Length:519500 Min. :45.30
## 1st Qu.:1931457 Class :character Class :character 1st Qu.:45.52
## Median :3174711 Mode :character Mode :character Median :45.52
## Mean :3262798 Mean :45.52
## 3rd Qu.:4306887 3rd Qu.:45.53
## Max. :6145437 Max. :45.64
## NA's :412
## StartLongitude StartDate StartTime
## Min. :-123.1 Min. :2016-07-19 Length:519500
## 1st Qu.:-122.7 1st Qu.:2016-10-22 Class1:hms
## Median :-122.7 Median :2017-06-11 Class2:difftime
## Mean :-122.7 Mean :2017-05-01 Mode :numeric
## 3rd Qu.:-122.7 3rd Qu.:2017-09-02
## Max. :-121.7 Max. :2018-03-31
## NA's :412
## EndHub EndLatitude EndLongitude EndDate
## Length:519500 Min. :34.26 Min. :-134.4 Length:519500
## Class :character 1st Qu.:45.52 1st Qu.:-122.7 Class :character
## Mode :character Median :45.52 Median :-122.7 Mode :character
## Mean :45.52 Mean :-122.7
## 3rd Qu.:45.53 3rd Qu.:-122.7
## Max. :49.16 Max. :-118.6
## NA's :389 NA's :389
## EndTime TripType BikeID BikeName
## Length:519500 Length:519500 Min. : 5986 Length:519500
## Class1:hms Class :character 1st Qu.: 6300 Class :character
## Class2:difftime Mode :character Median : 6573 Mode :character
## Mode :numeric Mean : 6675
## 3rd Qu.: 7154
## Max. :19237
##
## Distance_Miles Duration RentalAccessPath MultipleRental
## Min. : 0.000 Length:519500 Length:519500 Mode :logical
## 1st Qu.: 0.760 Class1:hms Class :character FALSE:482833
## Median : 1.390 Class2:difftime Mode :character TRUE :36667
## Mean : 2.037 Mode :numeric
## 3rd Qu.: 2.500
## Max. :5257.620
##
## start_wday weekend
## Sun:78118 Length:519500
## Mon:66448 Class :character
## Tue:67493 Mode :character
## Wed:67604
## Thu:68072
## Fri:79410
## Sat:92355
# Cardinal directions, coordinates, colors
compass_df <- data.frame(card_dir = c("N", "NE", "E","SE",
"S", "SW", "W", "NW"),
x = c(0, 0.707, 1, 0.707,
0, -0.707, -1, -0.707),
y = c(1, 0.707, 0, -0.707,
-1, -0.707, 0, 0.707),
# compcolor = c("red", "orange", "chartreuse2", "green",
# "cyan2", "blue", "purple", "pink"),
hexcolor = c("#e71516",
"#FC4C02",
"#82ef31",
"#1eca32",
"#38e8e5",
"#c504f6", #"#0c8cf5", #"#0452f6",
"#0c8cf5", #"#9903fc", #"#6619c8",
"#e216a2"))
# Basic plot
ggplot(compass_df, aes(x = x, y = y, color = hexcolor)) +
scale_color_identity() +
geom_segment(aes(x = 0, y = 0, xend = x, yend = y),
size = 2, arrow = arrow()) +
geom_point(aes(x = 0, y = 0), size = 5, color = "white") +
theme(legend.position = "none",
panel.background = element_blank()) +
coord_fixed(ratio = 1)
# Plot using long skinny arrows to look similar to standard compass rose
ggplot(compass_df, aes(x = x, y = y, color = hexcolor)) +
scale_color_identity() +
geom_segment(aes(x = 0, y = 0, xend = x, yend = y),
size = 0,
arrow = arrow(length = unit(0.4, "native"),
type = "closed",
angle = 3)) +
geom_point(aes(x = 0, y = 0), size = 18, color = "white") +
#geom_text() +
theme(legend.position = "none",
panel.background = element_blank()) +
coord_fixed(ratio = 1)
Reduce bike data to trips with known GPS data.
Calculate delta longitude/latitude, or how far in each cardinal direction each bike traveled.
Round starting latitude/longitudes to nearest 2/100th (0.002, 0.004, 0.006, etc). This roughly pulls every coordinate within a downtown Portland block into a single point.
bikegps <- bike_parsed %>%
filter(!is.na(StartLatitude) &
!is.na(StartLongitude) &
!is.na(EndLatitude) &
!is.na(EndLongitude)) %>%
mutate(d_lat = EndLatitude - StartLatitude) %>%
mutate(d_lon = EndLongitude - StartLongitude) %>%
mutate(r_start_lat = round( #round off to 0.002, 0.004, 0.006 etc...
StartLatitude * 5, 2) /5) %>%
mutate(r_start_lon = round( #round off to 0.002, 0.004, 0.006 etc...
StartLongitude * 5, 2) /5)For bikes starting within a one-block radius, find the median change in latitude/longitude and count the number of rides, ignore starting points with fewer than 10 rides.
gps_sum <- bikegps %>%
filter(!is.na(r_start_lat)) %>%
group_by(r_start_lat, r_start_lon) %>%
summarise(rides = n(), d_lat = median(d_lat), d_lon = median(d_lon)) %>%
ungroup() %>%
filter(rides >= 10)
ggplot(gps_sum, aes(x = r_start_lon, y = r_start_lat)) +
geom_point(alpha = 0.2) +
geom_segment(aes(xend = r_start_lon + 0.25*d_lon, yend = r_start_lat + 0.25*d_lat), arrow = arrow(length = unit(0.1, "inches"))) +
coord_cartesian(xlim = c(-122.7, -122.62), ylim = c(45.49, 45.56))
- Morning (4am-10am)
- Midday (10am-4pm)
- Evening (4pm-10pm)
- Late Night (10pm-4am)
tod_bike <- bikegps %>%
mutate(time_of_day = factor(case_when(
between(hour(StartTime), 4, 9) ~ "Morning", #When the hour position of the start time is >= 4 and <= 9, call "Morning"
between(hour(StartTime), 10, 15) ~ "Midday",
between(hour(StartTime), 16, 21) ~ "Evening",
between(hour(StartTime), 22, 24) ~ "Late Night",
between(hour(StartTime), 0, 3) ~ "Late Night"),
levels = c("Late Night", "Morning", "Midday", "Evening"),
labels = c("Late Night (10pm-4am)", "Morning (4am-10am)", "Midday (10am-4pm)", "Evening (4pm-10pm)")
))
summary(tod_bike$time_of_day)## Late Night (10pm-4am) Morning (4am-10am) Midday (10am-4pm)
## 35388 74171 208377
## Evening (4pm-10pm)
## 201144
Group data by starting point, time of day, and weekday/weekend status. Calculate median lat/lon change, remove points with fewer than 10 rides at that start point / time of day / weekend status group.
tod_bike_sum <- tod_bike %>%
group_by(r_start_lat, r_start_lon, time_of_day, weekend) %>%
summarise(rides = n(), d_lat = median(d_lat), d_lon = median(d_lon)) %>%
filter(rides >= 10)Determine primary cardinal/ordinal direction (N, NE, E, SE, S, SW, W, NW) for the median ride from each starting point. Join with prior dataframe containing color choices
tod_card <- tod_bike_sum %>%
#atan2(y, x) gives the angle of a point relative to the origin in radians
#atan2(y, x) * 180 / pi gives the angle in degrees
#a flat line to the right ("east") is 0, up ("north") is 90, down ("south") is -90, and left ("west") is 180/-180
mutate(d_angle = (atan2(d_lat, d_lon) * 180) / pi) %>%
mutate(card_dir = case_when(
d_angle <= 22.5 & d_angle > -22.5 ~ "E",
d_angle <= -22.5 & d_angle > -67.5 ~ "SE",
d_angle <= -67.5 & d_angle > -112.5 ~ "S",
d_angle <= -112.5 & d_angle > -157.5 ~ "SW",
d_angle <= -157.5 | d_angle > 157.5 ~ "W",
d_angle <= 157.5 & d_angle > 112.5 ~ "NW",
d_angle <= 112.5 & d_angle > 67.5 ~ "N",
d_angle <= 67.5 & d_angle > 22.5 ~ "NE")) %>%
left_join(compass_df, by = "card_dir")## Warning: Column `card_dir` joining character vector and factor, coercing
## into character vector
Fetch map from Stamen maps using ggmap, using empirically determined lat/lon coordinates for the data
left <- -122.71
bottom <- 45.499
right <- -122.610
top <- 45.561
custom_bound_box <- c(left, bottom, right, top)
names(custom_bound_box) <- c("left", "bottom", "right", "top")
# "Toner-lines" chosen for not having street labels, even though the contrast is higher, which we will cover with transparency
custompdxmap <- get_map(location = custom_bound_box, maptype = "toner-lines")## maptype = "toner-lines" is only available with source = "stamen".
## resetting to source = "stamen"...
## Source : http://tile.stamen.com/toner-lines/13/1303/2928.png
## Source : http://tile.stamen.com/toner-lines/13/1304/2928.png
## Source : http://tile.stamen.com/toner-lines/13/1305/2928.png
## Source : http://tile.stamen.com/toner-lines/13/1303/2929.png
## Source : http://tile.stamen.com/toner-lines/13/1304/2929.png
## Source : http://tile.stamen.com/toner-lines/13/1305/2929.png
## Source : http://tile.stamen.com/toner-lines/13/1303/2930.png
## Source : http://tile.stamen.com/toner-lines/13/1304/2930.png
## Source : http://tile.stamen.com/toner-lines/13/1305/2930.png
# Separate dataframe for the coordinates above, used to create transparency layer over map
fade_box <- data.frame(lat = c(left, right, right, left),
lon = c(bottom, bottom, top, top))Impact font for title, Arial for remaining text, both chosen for similarity to BIKETOWN branding
ggmap(custompdxmap,
# The base_layer is essential to properly facet_wrap the plotted data
base_layer = ggplot(data = tod_card %>% filter(weekend == "Weekday"), #subset data to only Weekdays, weekends are less consistent
aes(xend = r_start_lon + 0.25*d_lon, # Scale the delta in lat/long by 25% to reduce length of lines
yend = r_start_lat + 0.25*d_lat,
x = r_start_lon,
y = r_start_lat,
color = hexcolor))) + #Pull colors direct from compass rose choices above
# Prior to plotting segments, add a semitransparent box to give a dark background and reduce the visual noise of the map
geom_polygon(data = fade_box,
aes(x = lat,
y = lon),
fill = "black",
alpha = 0.7,
# "inhterit.aes = FALSE" is essential for this to plot, given the aesthetics set above
inherit.aes = FALSE) +
# Draw every given line/arrow
geom_segment(size = 0.5,
arrow = arrow(length = unit(0.1, "inches"),
angle = 20)) +
# Set the colors to exactly as given in the dataset
scale_color_identity() +
# Maintain a 1-to-1 size of x and y points
coord_fixed(ratio = 1) +
# Generally remove axis, ticks, labels, etc
theme_map() +
# Draw small circle around CascadiaRConf location - OHSU CLSB
geom_point(aes(x = -122.672, y = 45.503), size = 4, pch = 1, color = "white") +
# Text labeling CascadiaRConf location
geom_text_repel(data = data.frame(x = -122.672, y = 45.503, label = "You are\nhere"),
aes(x = x, y = y, label = label),
arrow = arrow(length = unit(0.08, "inches"), type = "closed"),
segment.size = 0.5,
nudge_x = -0.02,
#nudge_y = -0.001,
color = medbkgd,
point.padding = 1,
# "inhterit.aes = FALSE" is essential for this to plot, given global aesthetics
inherit.aes = FALSE,
family = "Arial") +
# Wrap data by portion of day
facet_wrap(~time_of_day) +
# Draw compass rose
geom_segment(data = compass_df,
# "inhterit.aes = FALSE" is essential for this to plot, given global aesthetics
inherit.aes = FALSE,
# The coordinates for the compass rose are set relative to an empirically chosen point in the upper-right
# The size of the lines are scaled to an empirically determined amount (1/200th) for appearance
aes(x = -122.624, y = 45.553,
xend = -122.624 + (x / 200),
yend = 45.553 + (y / 200),
color = hexcolor),
size = 0,
# Thin, long, closed arrowheads
arrow = arrow(length = unit(0.1, "native"),
type = "closed",
angle = 8)) +
# Off-White dot at center of compass rose, also obscures overlap of different colors
geom_point(aes(x = -122.624, y = 45.553), size = 8, color = medbkgd) +
# Set colors and text to mimic BIKETOWN branding
theme(strip.background = element_rect(fill = darkgray),
strip.text = element_text(color = bikeorange, face = "bold",
size = 14, family = "Arial"),
panel.border = element_rect(color = darkgray, fill = NA, size = 1),
#plot.background = element_rect(fill = bikeorange), #This is a really cool variation, gives an orange hue to the whole plot
plot.title = element_text(size = 38, hjust = 0.5,
family = "Impact"),
plot.subtitle = element_text(size = 12, family = "Arial",
hjust = 0.5),
plot.caption = element_text(size = 12, family = "Arial")) +
# Title, subtitle, caption
labs(title = "AVERAGE BIKETOWN TRIPS",
subtitle = "Median trajectory of weekday trips (2016-2018)",
caption = paste("Arrows represent median destination of 10 or more rides starting within a one-block radius (length of rides are 1/4 scale)",
"R & Rstudio, tidyverse & ggplot2, lubridate, ggmap & Stamen maps, ggrepel, extrafont, BIKETOWN system data",
"Kevin Watanabe-Smith for CascadiaRConf 2018 - github.com/WatanabeSmith/BIKETOWN_CascadiaR",
sep = "\n"))## Warning: Removed 75 rows containing missing values (geom_segment).
# Saving image
ggsave("Biketown_trajectories_WatanabeSmith.png", height = 11.2, width = 15.4) # Size set as same ratio as 8.5 x 11## Warning: Removed 75 rows containing missing values (geom_segment).
# Saving pdf
ggsave("Biketown_trajectories_WatanabeSmith.pdf", height = 11.2, width = 15.4,
# "device = cairo_pdf" fixes issue of fonts not appearing in PDF version
device = cairo_pdf)## Warning: Removed 75 rows containing missing values (geom_segment).
sessionInfo()## R version 3.5.0 (2018-04-23)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 17134)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=English_United States.1252
## [2] LC_CTYPE=English_United States.1252
## [3] LC_MONETARY=English_United States.1252
## [4] LC_NUMERIC=C
## [5] LC_TIME=English_United States.1252
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] bindrcpp_0.2.2 extrafont_0.17 ggrepel_0.7.0 ggthemes_3.4.0
## [5] ggmap_2.7.900 lubridate_1.7.4 forcats_0.3.0 stringr_1.3.0
## [9] dplyr_0.7.4 purrr_0.2.4 readr_1.1.1 tidyr_0.8.0
## [13] tibble_1.4.2 ggplot2_2.2.1 tidyverse_1.2.1
##
## loaded via a namespace (and not attached):
## [1] reshape2_1.4.3 haven_1.1.1 lattice_0.20-35
## [4] colorspace_1.3-2 htmltools_0.3.6 yaml_2.1.19
## [7] utf8_1.1.3 rlang_0.2.0 pillar_1.2.2
## [10] foreign_0.8-70 glue_1.2.0 modelr_0.1.1
## [13] readxl_1.1.0 jpeg_0.1-8 bindr_0.1.1
## [16] plyr_1.8.4 munsell_0.4.3 gtable_0.2.0
## [19] cellranger_1.1.0 rvest_0.3.2 RgoogleMaps_1.4.1
## [22] psych_1.7.8 evaluate_0.10.1 labeling_0.3
## [25] knitr_1.20 parallel_3.5.0 Rttf2pt1_1.3.6
## [28] broom_0.4.4 Rcpp_0.12.17 scales_0.5.0.9000
## [31] backports_1.1.2 jsonlite_1.5 mnormt_1.5-5
## [34] rjson_0.2.19 hms_0.4.2 png_0.1-7
## [37] digest_0.6.15 stringi_1.2.2 grid_3.5.0
## [40] rprojroot_1.3-2 cli_1.0.0 tools_3.5.0
## [43] bitops_1.0-6 magrittr_1.5 lazyeval_0.2.1
## [46] extrafontdb_1.0 crayon_1.3.4 pkgconfig_2.0.1
## [49] xml2_1.2.0 assertthat_0.2.0 rmarkdown_1.9
## [52] httr_1.3.1 rstudioapi_0.7 R6_2.2.2
## [55] nlme_3.1-137 compiler_3.5.0