Carlsbad-Blvd
setwd("C:/Users/s-das/Syncplicity Folders/MY_Projects/NCHRP 17-76/04102017/Data Sources/INRIX/")
a01 <- read.csv("C/Carlsbad-Blvd-entire-length-9-11-16.csv")
str(a01)
## 'data.frame': 108864 obs. of 9 variables:
## $ tmc_code : Factor w/ 54 levels "106-13652","106-13653",..: 3 41 49 10 45 40 27 47 36 42 ...
## $ measurement_tstamp : Factor w/ 2016 levels "9/11/2016 0:00",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ speed : num 21 25 22 30 22 35 32 44 40 33 ...
## $ average_speed : int 21 25 22 30 22 35 32 44 40 33 ...
## $ reference_speed : int 20 22 16 29 31 31 32 40 36 34 ...
## $ travel_time_minutes: num 1.3 0.04 0.04 1.6 0.13 0.01 3.74 0.28 0.5 0.03 ...
## $ confidence_score : num 20 20 20 20 20 20 20 20 20 20 ...
## $ cvalue : num 0 0 0 0 0 0 0 0 0 0 ...
## $ tmc1 : Factor w/ 54 levels "TMC106-13652",..: 3 41 49 10 45 40 27 47 36 42 ...
a02 <- read.csv("C/TMC_Identification1.csv")
a03 <- merge(a01, a02, by="tmc1")
dim(a01)
## [1] 108864 9
dim(a02)
## [1] 54 14
dim(a03)
## [1] 108864 22
names(a03)
## [1] "tmc1" "tmc_code" "measurement_tstamp"
## [4] "speed" "average_speed" "reference_speed"
## [7] "travel_time_minutes" "confidence_score" "cvalue"
## [10] "tmc" "road" "direction"
## [13] "intersection" "state" "county"
## [16] "zip" "start_latitude" "start_longitude"
## [19] "end_latitude" "end_longitude" "miles"
## [22] "road_order"
table(a03$direction)
##
## NORTHBOUND SOUTHBOUND
## 54432 54432
library(lubridate)
##
## Attaching package: 'lubridate'
## The following object is masked from 'package:base':
##
## date
a03$Time <- format(as.POSIXct(strptime(a03$measurement_tstamp, "%m/%d/%Y %H:%M",tz="")) ,format = "%H:%M")
a03$Time1 <- as.POSIXct(a03$Time, format = "%H:%M")
a03$Date <- format(as.POSIXct(strptime(a03$measurement_tstamp, "%m/%d/%Y %H:%M",tz="")) ,format = "%Y-%m-%d")
a03$Time1 <- as.POSIXct(a03$Time, format = "%H:%M")
a03$Date1 <- as.Date(a03$Date)
a03$Day <- wday(a03$Date1, label = TRUE)
str(a03)
## 'data.frame': 108864 obs. of 27 variables:
## $ tmc1 : Factor w/ 54 levels "TMC106-13652",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ tmc_code : Factor w/ 54 levels "106-13652","106-13653",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ measurement_tstamp : Factor w/ 2016 levels "9/11/2016 0:00",..: 1515 1238 1355 1036 1893 371 1257 18 45 1460 ...
## $ speed : num 14 24.2 27 27.2 27 ...
## $ average_speed : int 21 21 27 28 26 24 22 28 22 25 ...
## $ reference_speed : int 28 28 28 28 28 28 28 28 28 28 ...
## $ travel_time_minutes: num 4.17 2.42 2.16 2.15 2.16 2.26 2.65 2.08 2.94 2.33 ...
## $ confidence_score : num 30 30 20 28 30 30 20 20 30 20 ...
## $ cvalue : num 63.4 100 0 80 100 100 0 0 100 0 ...
## $ tmc : Factor w/ 54 levels "106-13652","106-13653",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ road : Factor w/ 1 level "CR-S21": 1 1 1 1 1 1 1 1 1 1 ...
## $ direction : Factor w/ 2 levels "NORTHBOUND","SOUTHBOUND": 2 2 2 2 2 2 2 2 2 2 ...
## $ intersection : Factor w/ 18 levels "4TH ST/DEL MAR HEIGHTS RD",..: 17 17 17 17 17 17 17 17 17 17 ...
## $ state : Factor w/ 1 level "CA": 1 1 1 1 1 1 1 1 1 1 ...
## $ county : Factor w/ 1 level "SAN DIEGO": 1 1 1 1 1 1 1 1 1 1 ...
## $ zip : int 92054 92054 92054 92054 92054 92054 92054 92054 92054 92054 ...
## $ start_latitude : num 33.2 33.2 33.2 33.2 33.2 ...
## $ start_longitude : num -117 -117 -117 -117 -117 ...
## $ end_latitude : num 33.2 33.2 33.2 33.2 33.2 ...
## $ end_longitude : num -117 -117 -117 -117 -117 ...
## $ miles : num 0.973 0.973 0.973 0.973 0.973 ...
## $ road_order : num 7 7 7 7 7 7 7 7 7 7 ...
## $ Time : chr "14:10" "15:05" "23:50" "21:15" ...
## $ Time1 : POSIXct, format: "2017-04-13 14:10:00" "2017-04-13 15:05:00" ...
## $ Date : chr "2016-09-16" "2016-09-15" "2016-09-15" "2016-09-14" ...
## $ Date1 : Date, format: "2016-09-16" "2016-09-15" ...
## $ Day : Ord.factor w/ 7 levels "Sun"<"Mon"<"Tues"<..: 6 5 5 4 7 2 5 1 1 6 ...
aa1 <- subset(a03, direction=="NORTHBOUND")
aa3 <- subset(a03, direction=="SOUTHBOUND")
require(ggplot2)
## Loading required package: ggplot2
require(scales)
## Loading required package: scales
ggplot(aa1, aes(x=Time1, y=speed)) +
geom_point(size=.9, alpha = 0.05, colour="green") +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M"))+theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Carlsbad Blvd (Northbound)")
ggplot(aa1, aes(x=Time1, y=speed, colour=Day)) +
geom_point(size=.5, alpha = 0.1) +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Carlsbad Blvd (Northbound)")
ggplot(aa3, aes(x=Time1, y=speed)) +
geom_point(size=.9, alpha = 0.05, colour="green") +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M"))+theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Carlsbad Blvd (Southbound)")
ggplot(aa3, aes(x=Time1, y=speed, colour=Day)) +
geom_point(size=.5, alpha = 0.1) +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Carlsbad Blvd (Southbound)")
aa2 <- aggregate(speed ~ Time1+direction+Day, a03, mean)
head(aa2)
## Time1 direction Day speed
## 1 2017-04-13 00:00:00 NORTHBOUND Sun 31.36963
## 2 2017-04-13 00:05:00 NORTHBOUND Sun 31.30259
## 3 2017-04-13 00:10:00 NORTHBOUND Sun 31.27370
## 4 2017-04-13 00:15:00 NORTHBOUND Sun 31.31037
## 5 2017-04-13 00:20:00 NORTHBOUND Sun 31.44444
## 6 2017-04-13 00:25:00 NORTHBOUND Sun 31.37481
dim(aa1)
## [1] 54432 27
dim(aa2)
## [1] 4032 4
colnames(aa2)[2] <- "Direction"
ggplot(aa2, aes(x=Time1, y=speed, colour=Direction)) +
geom_path() + geom_point(cex=0.4)+
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)")
Kearny-Villa-Rd
setwd("C:/Users/s-das/Syncplicity Folders/MY_Projects/NCHRP 17-76/04102017/Data Sources/INRIX/")
a01 <- read.csv("K/Kearny-Villa-Rd-entire-length-9-11-16.csv")
str(a01)
## 'data.frame': 64512 obs. of 9 variables:
## $ tmc_code : Factor w/ 32 levels "106-11852","106-11853",..: 11 5 20 30 26 12 14 1 16 18 ...
## $ measurement_tstamp : Factor w/ 2016 levels "9/11/2016 0:00",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ speed : num 25 56 35 56 28 52 61 32 21 29 ...
## $ average_speed : int 25 56 35 56 28 52 61 38 21 29 ...
## $ reference_speed : int 27 56 33 57 22 47 59 34 21 23 ...
## $ travel_time_minutes: num 2.49 0.08 0.27 0.45 0.56 0.95 0.91 2.26 1.1 0.55 ...
## $ confidence_score : num 20 20 20 20 20 20 20 30 20 20 ...
## $ cvalue : num 0 0 0 0 0 0 0 100 0 0 ...
## $ tmc1 : Factor w/ 32 levels "TMC106-11852",..: 11 5 20 30 26 12 14 1 16 18 ...
a02 <- read.csv("K/TMC_Identification2.csv")
a03 <- merge(a01, a02, by="tmc1")
dim(a01)
## [1] 64512 9
dim(a02)
## [1] 32 14
dim(a03)
## [1] 64512 22
names(a03)
## [1] "tmc1" "tmc_code" "measurement_tstamp"
## [4] "speed" "average_speed" "reference_speed"
## [7] "travel_time_minutes" "confidence_score" "cvalue"
## [10] "tmc" "road" "direction"
## [13] "intersection" "state" "county"
## [16] "zip" "start_latitude" "start_longitude"
## [19] "end_latitude" "end_longitude" "miles"
## [22] "road_order"
table(a03$direction)
##
## NORTHBOUND SOUTHBOUND
## 32256 32256
library(lubridate)
a03$Time <- format(as.POSIXct(strptime(a03$measurement_tstamp, "%m/%d/%Y %H:%M",tz="")) ,format = "%H:%M")
a03$Time1 <- as.POSIXct(a03$Time, format = "%H:%M")
a03$Date <- format(as.POSIXct(strptime(a03$measurement_tstamp, "%m/%d/%Y %H:%M",tz="")) ,format = "%Y-%m-%d")
a03$Time1 <- as.POSIXct(a03$Time, format = "%H:%M")
a03$Date1 <- as.Date(a03$Date)
a03$Day <- wday(a03$Date1, label = TRUE)
str(a03)
## 'data.frame': 64512 obs. of 27 variables:
## $ tmc1 : Factor w/ 32 levels "TMC106-11852",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ tmc_code : Factor w/ 32 levels "106-11852","106-11853",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ measurement_tstamp : Factor w/ 2016 levels "9/11/2016 0:00",..: 920 1988 1606 1562 1405 1442 1482 478 1257 550 ...
## $ speed : num 35 26 37 25.6 33 ...
## $ average_speed : int 31 32 37 32 33 36 33 34 29 30 ...
## $ reference_speed : int 34 34 34 34 34 34 34 34 34 34 ...
## $ travel_time_minutes: num 2.06 2.78 1.95 2.82 2.19 2.01 2.46 2.19 3.04 2.93 ...
## $ confidence_score : num 30 30 20 30 20 20 30 30 30 30 ...
## $ cvalue : num 100 100 0 100 0 0 100 97.2 100 100 ...
## $ tmc : Factor w/ 32 levels "106-11852","106-11853",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ road : Factor w/ 1 level "KEARNY VILLA RD": 1 1 1 1 1 1 1 1 1 1 ...
## $ direction : Factor w/ 2 levels "NORTHBOUND","SOUTHBOUND": 2 2 2 2 2 2 2 2 2 2 ...
## $ intersection : Factor w/ 9 levels "CA-163","CA-274/BALBOA AVE",..: 7 7 7 7 7 7 7 7 7 7 ...
## $ state : Factor w/ 1 level "CA": 1 1 1 1 1 1 1 1 1 1 ...
## $ county : Factor w/ 1 level "SAN DIEGO": 1 1 1 1 1 1 1 1 1 1 ...
## $ zip : int 92123 92123 92123 92123 92123 92123 92123 92123 92123 92123 ...
## $ start_latitude : num 32.8 32.8 32.8 32.8 32.8 ...
## $ start_longitude : num -117 -117 -117 -117 -117 ...
## $ end_latitude : num 32.8 32.8 32.8 32.8 32.8 ...
## $ end_longitude : num -117 -117 -117 -117 -117 ...
## $ miles : num 1.2 1.2 1.2 1.2 1.2 ...
## $ road_order : int 15 15 15 15 15 15 15 15 15 15 ...
## $ Time : chr "12:35" "07:35" "20:45" "18:05" ...
## $ Time1 : POSIXct, format: "2017-04-13 12:35:00" "2017-04-13 07:35:00" ...
## $ Date : chr "2016-09-14" "2016-09-17" "2016-09-16" "2016-09-16" ...
## $ Date1 : Date, format: "2016-09-14" "2016-09-17" ...
## $ Day : Ord.factor w/ 7 levels "Sun"<"Mon"<"Tues"<..: 4 7 6 6 5 6 6 2 5 2 ...
aa1 <- subset(a03, direction=="NORTHBOUND")
aa3 <- subset(a03, direction=="SOUTHBOUND")
require(ggplot2)
require(scales)
ggplot(aa1, aes(x=Time1, y=speed)) +
geom_point(size=.9, alpha = 0.05, colour="green") +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M"))+theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Kearny Villa Rd (Northbound)")
ggplot(aa1, aes(x=Time1, y=speed, colour=Day)) +
geom_point(size=.5, alpha = 0.1) +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Kearny Villa Rd (Northbound)")
ggplot(aa3, aes(x=Time1, y=speed)) +
geom_point(size=.9, alpha = 0.05, colour="green") +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M"))+theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Kearny Villa Rd (Southbound)")
ggplot(aa3, aes(x=Time1, y=speed, colour=Day)) +
geom_point(size=.5, alpha = 0.1) +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Kearny Villa Rd (Southbound)")
aa2 <- aggregate(speed ~ Time1+direction+Day, a03, mean)
head(aa2)
## Time1 direction Day speed
## 1 2017-04-13 00:00:00 NORTHBOUND Sun 36.75
## 2 2017-04-13 00:05:00 NORTHBOUND Sun 36.75
## 3 2017-04-13 00:10:00 NORTHBOUND Sun 36.75
## 4 2017-04-13 00:15:00 NORTHBOUND Sun 36.75
## 5 2017-04-13 00:20:00 NORTHBOUND Sun 36.75
## 6 2017-04-13 00:25:00 NORTHBOUND Sun 36.75
dim(aa1)
## [1] 32256 27
dim(aa2)
## [1] 4032 4
colnames(aa2)[2] <- "Direction"
ggplot(aa2, aes(x=Time1, y=speed, colour=Direction)) +
geom_path() + geom_point(cex=0.4)+
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)")
Nimitz-Blvd
setwd("C:/Users/s-das/Syncplicity Folders/MY_Projects/NCHRP 17-76/04102017/Data Sources/INRIX/")
a01 <- read.csv("N/Nimitz-Blvd-entire-length-9-11-16.csv")
str(a01)
## 'data.frame': 32256 obs. of 9 variables:
## $ tmc_code : Factor w/ 16 levels "106-14016","106-14017",..: 16 7 13 4 9 1 2 3 5 14 ...
## $ measurement_tstamp : Factor w/ 2016 levels "9/11/2016 0:00",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ speed : num 19 36.1 36 29 9 ...
## $ average_speed : int 19 35 36 22 9 24 31 38 27 12 ...
## $ reference_speed : int 18 40 36 19 13 24 29 37 25 14 ...
## $ travel_time_minutes: num 0.28 1.54 0.01 0.44 0.06 0.8 1.31 1.45 0.72 0.04 ...
## $ confidence_score : num 20 22 10 30 20 20 20 30 20 20 ...
## $ cvalue : num 0 19.2 0 22.6 0 0 0 95.8 0 0 ...
## $ tmc1 : Factor w/ 16 levels "TMC106-14016",..: 16 7 13 4 9 1 2 3 5 14 ...
a02 <- read.csv("N/TMC_Identification3.csv")
a03 <- merge(a01, a02, by="tmc1")
dim(a01)
## [1] 32256 9
dim(a02)
## [1] 16 14
dim(a03)
## [1] 32256 22
names(a03)
## [1] "tmc1" "tmc_code" "measurement_tstamp"
## [4] "speed" "average_speed" "reference_speed"
## [7] "travel_time_minutes" "confidence_score" "cvalue"
## [10] "tmc" "road" "direction"
## [13] "intersection" "state" "county"
## [16] "zip" "start_latitude" "start_longitude"
## [19] "end_latitude" "end_longitude" "miles"
## [22] "road_order"
table(a03$direction)
##
## NORTHBOUND SOUTHBOUND
## 16128 16128
library(lubridate)
a03$Time <- format(as.POSIXct(strptime(a03$measurement_tstamp, "%m/%d/%Y %H:%M",tz="")) ,format = "%H:%M")
a03$Time1 <- as.POSIXct(a03$Time, format = "%H:%M")
a03$Date <- format(as.POSIXct(strptime(a03$measurement_tstamp, "%m/%d/%Y %H:%M",tz="")) ,format = "%Y-%m-%d")
a03$Time1 <- as.POSIXct(a03$Time, format = "%H:%M")
a03$Date1 <- as.Date(a03$Date)
a03$Day <- wday(a03$Date1, label = TRUE)
str(a03)
## 'data.frame': 32256 obs. of 27 variables:
## $ tmc1 : Factor w/ 16 levels "TMC106-14016",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ tmc_code : Factor w/ 16 levels "106-14016","106-14017",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ measurement_tstamp : Factor w/ 2016 levels "9/11/2016 0:00",..: 1885 142 1370 587 954 262 370 746 1983 1318 ...
## $ speed : num 18.4 26 24.7 23 31 ...
## $ average_speed : int 20 26 26 23 21 26 19 26 25 23 ...
## $ reference_speed : int 24 24 24 24 24 24 24 24 24 24 ...
## $ travel_time_minutes: num 1.05 0.74 0.78 0.84 0.62 0.74 0.77 0.74 0.77 0.74 ...
## $ confidence_score : num 28 20 24 20 30 20 30 20 20 30 ...
## $ cvalue : num 80 0 40 0 96.4 0 100 0 0 100 ...
## $ tmc : Factor w/ 16 levels "106-14016","106-14017",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ road : Factor w/ 1 level "NIMITZ BLVD": 1 1 1 1 1 1 1 1 1 1 ...
## $ direction : Factor w/ 2 levels "NORTHBOUND","SOUTHBOUND": 2 2 2 2 2 2 2 2 2 2 ...
## $ intersection : Factor w/ 5 levels "CA-209/ROSECRANS ST",..: 4 4 4 4 4 4 4 4 4 4 ...
## $ state : Factor w/ 1 level "CA": 1 1 1 1 1 1 1 1 1 1 ...
## $ county : Factor w/ 1 level "SAN DIEGO": 1 1 1 1 1 1 1 1 1 1 ...
## $ zip : int 92106 92106 92106 92106 92106 92106 92106 92106 92106 92106 ...
## $ start_latitude : num 32.7 32.7 32.7 32.7 32.7 ...
## $ start_longitude : num -117 -117 -117 -117 -117 ...
## $ end_latitude : num 32.7 32.7 32.7 32.7 32.7 ...
## $ end_longitude : num -117 -117 -117 -117 -117 ...
## $ miles : num 0.32 0.32 0.32 0.32 0.32 ...
## $ road_order : int 6 6 6 6 6 6 6 6 6 6 ...
## $ Time : chr "20:00" "19:45" "04:05" "00:50" ...
## $ Time1 : POSIXct, format: "2017-04-13 20:00:00" "2017-04-13 19:45:00" ...
## $ Date : chr "2016-09-17" "2016-09-11" "2016-09-15" "2016-09-13" ...
## $ Date1 : Date, format: "2016-09-17" "2016-09-11" ...
## $ Day : Ord.factor w/ 7 levels "Sun"<"Mon"<"Tues"<..: 7 1 5 3 4 1 2 3 7 5 ...
aa1 <- subset(a03, direction=="NORTHBOUND")
aa3 <- subset(a03, direction=="SOUTHBOUND")
require(ggplot2)
require(scales)
ggplot(aa1, aes(x=Time1, y=speed)) +
geom_point(size=.9, alpha = 0.05, colour="green") +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M"))+theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Nimitz Blvd (Northbound)")
ggplot(aa1, aes(x=Time1, y=speed, colour=Day)) +
geom_point(size=.5, alpha = 0.1) +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Nimitz Blvd (Northbound)")
ggplot(aa3, aes(x=Time1, y=speed)) +
geom_point(size=.9, alpha = 0.05, colour="green") +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M"))+theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Nimitz Blvd (Southbound)")
ggplot(aa3, aes(x=Time1, y=speed, colour=Day)) +
geom_point(size=.5, alpha = 0.1) +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Nimitz Blvd (Southbound)")
aa2 <- aggregate(speed ~ Time1+direction+Day, a03, mean)
head(aa2)
## Time1 direction Day speed
## 1 2017-04-13 00:00:00 NORTHBOUND Sun 25.77500
## 2 2017-04-13 00:05:00 NORTHBOUND Sun 24.90750
## 3 2017-04-13 00:10:00 NORTHBOUND Sun 24.62500
## 4 2017-04-13 00:15:00 NORTHBOUND Sun 23.75125
## 5 2017-04-13 00:20:00 NORTHBOUND Sun 23.62500
## 6 2017-04-13 00:25:00 NORTHBOUND Sun 23.62500
dim(aa1)
## [1] 16128 27
dim(aa2)
## [1] 4032 4
colnames(aa2)[2] <- "Direction"
ggplot(aa2, aes(x=Time1, y=speed, colour=Direction)) +
geom_path() + geom_point(cex=0.4)+
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)")
