As with the Enlgish commuting data, we begin by loading and inspecting the raw commuting data. As we shall see, it is in a different format than the English data, so needs to be treated differently. In addition, we need to translate some of the Dutch words into English, using the command gsub. As with the English data, the information was taken from an official data dissemination portal, in this case the CBS. The data is publicly available on the internet.
nm <- read.csv("NL-Data/2011netherlands.csv", sep = ";") # This is the Dutch commuting data, downloaded from the CBS
head(nm)
## Vervoerwijzen Totaal.vervoerwijzen Auto..bestuurder. Auto..passagier.
## 1 Reg aantal aantal aantal
## 2 Nederland 0.49 0.26 0.02
## 3 Groningen 0.46 0.23 0.02
## 4 Friesland 0.47 0.27 0.03
## 5 Drenthe 0.52 0.31 0.03
## 6 Overijssel 0.51 0.27 0.02
## Trein Bus.tram.metro Brom..snorfiets Fiets Lopen
## 1 aantal aantal aantal aantal aantal
## 2 0.02 0.02 0.01 0.12 0.03
## 3 0 0 0 0.15 0.02
## 4 0 0 0 0.12 0.02
## 5 0 0 0 0.12 0.02
## 6 0 0 0 0.15 0.02
## Overige.vervoerwijzen Totaal.vervoerwijzen.1 Auto..bestuurder..1
## 1 aantal km km
## 2 0.01 17.75 23.86
## 3 0 18.82 27.77
## 4 0 17.94 24.56
## 5 0 19.81 23.48
## 6 0 18.74 25.23
## Auto..passagier..1 Trein.1 Bus.tram.metro.1 Brom..snorfiets.1 Fiets.1
## 1 km km km km km
## 2 24.97 38.35 13.37 8.75 4.5
## 3 33.8 0 0 0 4.05
## 4 35.61 0 0 0 3.42
## 5 39.54 0 0 0 4.41
## 6 19.49 0 0 0 4.28
## Lopen.1 Overige.vervoerwijzen.1 Totaal.vervoerwijzen.2
## 1 km km minuten
## 2 2.68 22.59 27.39
## 3 3.13 0 26.53
## 4 1.94 0 23.35
## 5 2.32 0 23.82
## 6 2 0 25.3
## Auto..bestuurder..2 Auto..passagier..2 Trein.2 Bus.tram.metro.2
## 1 minuten minuten minuten minuten
## 2 28.89 31.78 64.48 42.4
## 3 29.14 31.81 0 0
## 4 26.33 32.94 0 0
## 5 24.29 35.93 0 0
## 6 28.05 26.6 0 0
## Brom..snorfiets.2 Fiets.2 Lopen.2 Overige.vervoerwijzen.2
## 1 minuten minuten minuten minuten
## 2 19.8 18.46 12.38 30.56
## 3 0 19.29 17.65 0
## 4 0 13.9 23.55 0
## 5 0 15.82 11.58 0
## 6 0 15.22 7.74 0
agrep(pattern = " (PV)", x = nm[, 1], )
## integer(0)
sub(pattern = " (PV)", replacement = "", x = as.character(nm[, 1])) # also don't work... calc
## [1] "Reg" "Nederland" "Groningen" "Friesland"
## [5] "Drenthe" "Overijssel" "Flevoland" "Gelderland"
## [9] "Utrecht" "Noord-Holland" "Zuid-Holland" "Zeeland"
## [13] "Noord-Brabant" "Limburg"
class(nm[, 1])
## [1] "factor"
head(nm)
## Vervoerwijzen Totaal.vervoerwijzen Auto..bestuurder. Auto..passagier.
## 1 Reg aantal aantal aantal
## 2 Nederland 0.49 0.26 0.02
## 3 Groningen 0.46 0.23 0.02
## 4 Friesland 0.47 0.27 0.03
## 5 Drenthe 0.52 0.31 0.03
## 6 Overijssel 0.51 0.27 0.02
## Trein Bus.tram.metro Brom..snorfiets Fiets Lopen
## 1 aantal aantal aantal aantal aantal
## 2 0.02 0.02 0.01 0.12 0.03
## 3 0 0 0 0.15 0.02
## 4 0 0 0 0.12 0.02
## 5 0 0 0 0.12 0.02
## 6 0 0 0 0.15 0.02
## Overige.vervoerwijzen Totaal.vervoerwijzen.1 Auto..bestuurder..1
## 1 aantal km km
## 2 0.01 17.75 23.86
## 3 0 18.82 27.77
## 4 0 17.94 24.56
## 5 0 19.81 23.48
## 6 0 18.74 25.23
## Auto..passagier..1 Trein.1 Bus.tram.metro.1 Brom..snorfiets.1 Fiets.1
## 1 km km km km km
## 2 24.97 38.35 13.37 8.75 4.5
## 3 33.8 0 0 0 4.05
## 4 35.61 0 0 0 3.42
## 5 39.54 0 0 0 4.41
## 6 19.49 0 0 0 4.28
## Lopen.1 Overige.vervoerwijzen.1 Totaal.vervoerwijzen.2
## 1 km km minuten
## 2 2.68 22.59 27.39
## 3 3.13 0 26.53
## 4 1.94 0 23.35
## 5 2.32 0 23.82
## 6 2 0 25.3
## Auto..bestuurder..2 Auto..passagier..2 Trein.2 Bus.tram.metro.2
## 1 minuten minuten minuten minuten
## 2 28.89 31.78 64.48 42.4
## 3 29.14 31.81 0 0
## 4 26.33 32.94 0 0
## 5 24.29 35.93 0 0
## 6 28.05 26.6 0 0
## Brom..snorfiets.2 Fiets.2 Lopen.2 Overige.vervoerwijzen.2
## 1 minuten minuten minuten minuten
## 2 19.8 18.46 12.38 30.56
## 3 0 19.29 17.65 0
## 4 0 13.9 23.55 0
## 5 0 15.82 11.58 0
## 6 0 15.22 7.74 0
names(nm) <- gsub(pattern = "Auto..passagier.", replacement = "Car.p", x = names(nm))
names(nm) <- gsub(pattern = "Auto..bestuurder.", replacement = "Car.d", x = names(nm))
names(nm) <- gsub(pattern = "Trein", replacement = "Train", x = names(nm))
names(nm) <- gsub("Brom..snorfiets", "Moto", x = names(nm))
names(nm) <- gsub(names(nm[8]), "Bicycle", x = names(nm))
names(nm) <- gsub(names(nm[9]), "Walk", x = names(nm))
names(nm) <- gsub(names(nm[10]), "Other", x = names(nm))
names(nm)
## [1] "Vervoerwijzen" "Totaal.vervoerwijzen"
## [3] "Car.d" "Car.p"
## [5] "Train" "Bus.tram.metro"
## [7] "Moto" "Bicycle"
## [9] "Walk" "Other"
## [11] "Totaal.vervoerwijzen.1" "Car.d.1"
## [13] "Car.p.1" "Train.1"
## [15] "Bus.tram.metro.1" "Moto.1"
## [17] "Bicycle.1" "Walk.1"
## [19] "Other.1" "Totaal.vervoerwijzen.2"
## [21] "Car.d.2" "Car.p.2"
## [23] "Train.2" "Bus.tram.metro.2"
## [25] "Moto.2" "Bicycle.2"
## [27] "Walk.2" "Other.2"
Now we take the processed Dutch data, and merge them with geographic data, saved as a shapefile:
library(rgeos) # ensure the right packages are installed
## Loading required package: sp
## rgeos version: 0.2-17, (SVN revision 392) GEOS runtime version:
## 3.3.8-CAPI-1.7.8 Polygon checking: TRUE
library(rgdal)
## rgdal: version: 0.8-9, (SVN revision 470) Geospatial Data Abstraction
## Library extensions to R successfully loaded Loaded GDAL runtime: GDAL
## 1.10.0, released 2013/04/24 but rgdal build and GDAL runtime not in sync:
## ... consider re-installing rgdal!! Path to GDAL shared files:
## /usr/share/gdal/1.10 Loaded PROJ.4 runtime: Rel. 4.8.0, 6 March 2012,
## [PJ_VERSION: 480] Path to PROJ.4 shared files: (autodetected)
setwd("NL-Data/")
regs <- readOGR(dsn = ".", layer = "Provinces")
## OGR data source with driver: ESRI Shapefile
## Source: ".", layer: "Provinces"
## with 13 features and 40 fields
## Feature type: wkbPolygon with 2 dimensions
setwd("../")
plot(regs) # distant islands present
r2 <- regs[2:nrow(regs@data), ] # remove 1st row, so only mainland regions present
plot(r2)
head(r2@data) # remove excess cols
## adm1_code Shape_Leng Shape_Area diss_me adm1_code_ iso_3166_2 wikipedia
## 1 NLD-3483 5.374 0.6741 3483 NLD-3483 NL- <NA>
## 2 NLD-3484 2.896 0.1830 3484 NLD-3484 NL- <NA>
## 3 NLD-3485 4.157 0.4175 3485 NLD-3485 NL- <NA>
## 4 NLD-3486 4.488 0.4624 3486 NLD-3486 NL- <NA>
## 5 NLD-894 2.964 0.3518 894 NLD-894 NL- <NA>
## 6 NLD-895 5.914 0.5265 895 NLD-895 NL- <NA>
## sr_sov_a3 sr_adm0_a3 iso_a2 adm0_sr admin0_lab name
## 1 NL1 NLD NL 1 6 Noord-Brabant
## 2 NL1 NLD NL 1 6 Utrecht
## 3 NL1 NLD NL 1 6 Zuid-Holland
## 4 NL1 NLD NL 5 6 Noord-Holland
## 5 NL1 NLD NL 1 6 Drenthe
## 6 NL1 NLD NL 5 6 Friesland
## name_alt
## 1 Brabante del Norte|Brabante do Norte|Brabante settentrionale|Brabant-septentrional|Nord-Brabant|Nort
## 2 <NA>
## 3 Hollande-mridionale|South Holland
## 4 Holanda do Norte|Hollande-septentrionale|North Holland
## 5 <NA>
## 6 Frise|Frisia|Frsia
## name_local type type_en code_local code_hasc note hasc_maybe
## 1 <NA> Provincie Province <NA> NL.NB <NA> <NA>
## 2 <NA> Provincie Province <NA> NL.UT <NA> <NA>
## 3 <NA> Provincie Province <NA> NL.ZH <NA> <NA>
## 4 <NA> Provincie Province <NA> NL.NH <NA> <NA>
## 5 <NA> Provincie Province <NA> NL.DR <NA> <NA>
## 6 <NA> Provincie Province <NA> NL.FR <NA> <NA>
## region region_cod region_big big_code provnum_ne gadm_level check_me
## 1 <NA> <NA> <NA> <NA> 0 1 0
## 2 <NA> <NA> <NA> <NA> 0 1 0
## 3 <NA> <NA> <NA> <NA> 0 1 0
## 4 <NA> <NA> <NA> <NA> 0 1 0
## 5 <NA> <NA> <NA> <NA> 7 1 0
## 6 <NA> <NA> <NA> <NA> 2 1 0
## scalerank datarank abbrev postal area_sqkm sameascity labelrank
## 1 8 8 <NA> <NA> 0 -99 8
## 2 8 8 <NA> <NA> 0 9 9
## 3 8 8 <NA> <NA> 0 -99 8
## 4 8 8 <NA> <NA> 0 -99 8
## 5 8 8 <NA> DR 0 -99 8
## 6 8 8 <NA> FR 0 -99 8
## featurecla admin name_len mapcolor9 mapcolor13
## 1 Admin-1 scale rank Netherlands 13 2 9
## 2 Admin-1 scale rank Netherlands 7 2 9
## 3 Admin-1 scale rank Netherlands 12 2 9
## 4 Admin-1 scale rank Netherlands 13 2 9
## 5 Admin-1 scale rank Netherlands 7 2 9
## 6 Admin-1 scale rank Netherlands 9 2 9
r2@data <- r2@data[, -c(1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15:18, 20:ncol(r2@data))]
# match-up names
r2@data
## Shape_Leng name code_hasc
## 1 5.374 Noord-Brabant NL.NB
## 2 2.896 Utrecht NL.UT
## 3 4.157 Zuid-Holland NL.ZH
## 4 4.488 Noord-Holland NL.NH
## 5 2.964 Drenthe NL.DR
## 6 5.914 Friesland NL.FR
## 7 5.820 Gelderland NL.GE
## 8 3.325 Groningen NL.GR
## 9 4.515 Limburg NL.LI
## 10 4.323 Overijssel NL.OV
## 11 2.675 Flevoland NL.FL
## 12 5.779 Zeeland NL.ZE
nm[, 1]
## [1] Reg Nederland Groningen Friesland Drenthe
## [6] Overijssel Flevoland Gelderland Utrecht Noord-Holland
## [11] Zuid-Holland Zeeland Noord-Brabant Limburg
## 14 Levels: Drenthe Flevoland Friesland Gelderland Groningen ... Zuid-Holland
nm <- nm[-2, ]
names(nm)
## [1] "Vervoerwijzen" "Totaal.vervoerwijzen"
## [3] "Car.d" "Car.p"
## [5] "Train" "Bus.tram.metro"
## [7] "Moto" "Bicycle"
## [9] "Walk" "Other"
## [11] "Totaal.vervoerwijzen.1" "Car.d.1"
## [13] "Car.p.1" "Train.1"
## [15] "Bus.tram.metro.1" "Moto.1"
## [17] "Bicycle.1" "Walk.1"
## [19] "Other.1" "Totaal.vervoerwijzen.2"
## [21] "Car.d.2" "Car.p.2"
## [23] "Train.2" "Bus.tram.metro.2"
## [25] "Moto.2" "Bicycle.2"
## [27] "Walk.2" "Other.2"
code2 <- strtrim(nm[, 1], width = 2)
nm$c2 <- toupper(code2)
c2 <- strsplit(as.character(r2$code_hasc), split = "[.]")
r2@data
## Shape_Leng name code_hasc
## 1 5.374 Noord-Brabant NL.NB
## 2 2.896 Utrecht NL.UT
## 3 4.157 Zuid-Holland NL.ZH
## 4 4.488 Noord-Holland NL.NH
## 5 2.964 Drenthe NL.DR
## 6 5.914 Friesland NL.FR
## 7 5.820 Gelderland NL.GE
## 8 3.325 Groningen NL.GR
## 9 4.515 Limburg NL.LI
## 10 4.323 Overijssel NL.OV
## 11 2.675 Flevoland NL.FL
## 12 5.779 Zeeland NL.ZE
r2@data$c2 <- unlist(c2)[seq(2, 24, 2)]
nm$Vervoerwijzen
## [1] Reg Groningen Friesland Drenthe Overijssel
## [6] Flevoland Gelderland Utrecht Noord-Holland Zuid-Holland
## [11] Zeeland Noord-Brabant Limburg
## 14 Levels: Drenthe Flevoland Friesland Gelderland Groningen ... Zuid-Holland
nm$c2
## [1] "RE" "GR" "FR" "DR" "OV" "FL" "GE" "UT" "NO" "ZU" "ZE" "NO" "LI"
r2$c2
## [1] "NB" "UT" "ZH" "NH" "DR" "FR" "GE" "GR" "LI" "OV" "FL" "ZE"
r2$name
## [1] Noord-Brabant Utrecht Zuid-Holland Noord-Holland Drenthe
## [6] Friesland Gelderland Groningen Limburg Overijssel
## [11] Flevoland Zeeland
## 13 Levels: Drenthe Flevoland Friesland Gelderland Groningen ... Zuid-Holland
merge(y = nm, x = r2@data, by = "c2") # test of the merge process...
## c2 Shape_Leng name code_hasc Vervoerwijzen Totaal.vervoerwijzen
## 1 DR 2.964 Drenthe NL.DR Drenthe 0.52
## 2 FL 2.675 Flevoland NL.FL Flevoland 0.52
## 3 FR 5.914 Friesland NL.FR Friesland 0.47
## 4 GE 5.820 Gelderland NL.GE Gelderland 0.51
## 5 GR 3.325 Groningen NL.GR Groningen 0.46
## 6 LI 4.515 Limburg NL.LI Limburg 0.48
## 7 OV 4.323 Overijssel NL.OV Overijssel 0.51
## 8 UT 2.896 Utrecht NL.UT Utrecht 0.5
## 9 ZE 5.779 Zeeland NL.ZE Zeeland 0.47
## Car.d Car.p Train Bus.tram.metro Moto Bicycle Walk Other
## 1 0.31 0.03 0 0 0 0.12 0.02 0
## 2 0.3 0.02 0 0 0 0.09 0.02 0
## 3 0.27 0.03 0 0 0 0.12 0.02 0
## 4 0.28 0.02 0 0 0 0.13 0.03 0
## 5 0.23 0.02 0 0 0 0.15 0.02 0
## 6 0.3 0.02 0 0 0 0.09 0.03 0
## 7 0.27 0.02 0 0 0 0.15 0.02 0
## 8 0.26 0 0 0 0 0.13 0.02 0
## 9 0.28 0.02 0 0 0 0.12 0.02 0
## Totaal.vervoerwijzen.1 Car.d.1 Car.p.1 Train.1 Bus.tram.metro.1 Moto.1
## 1 19.81 23.48 39.54 0 0 0
## 2 24.71 30.39 39.76 0 0 0
## 3 17.94 24.56 35.61 0 0 0
## 4 18.63 25.24 25.12 0 0 0
## 5 18.82 27.77 33.8 0 0 0
## 6 16.66 20.69 14.34 0 0 0
## 7 18.74 25.23 19.49 0 0 0
## 8 17.57 24.17 0 0 0 0
## 9 17.17 23.86 19.28 0 0 0
## Bicycle.1 Walk.1 Other.1 Totaal.vervoerwijzen.2 Car.d.2 Car.p.2 Train.2
## 1 4.41 2.32 0 23.82 24.29 35.93 0
## 2 3.67 3.64 0 33.09 33.25 49.47 0
## 3 3.42 1.94 0 23.35 26.33 32.94 0
## 4 4.57 1.74 0 26.92 29.33 30.41 0
## 5 4.05 3.13 0 26.53 29.14 31.81 0
## 6 4.52 2.29 0 24.63 25.75 20.32 0
## 7 4.28 2 0 25.3 28.05 26.6 0
## 8 5.11 2.32 0 28.91 31.02 0 0
## 9 3.32 1.46 0 22.92 26.05 39.79 0
## Bus.tram.metro.2 Moto.2 Bicycle.2 Walk.2 Other.2
## 1 0 0 15.82 11.58 0
## 2 0 0 13.69 9.38 0
## 3 0 0 13.9 23.55 0
## 4 0 0 18.33 9.14 0
## 5 0 0 19.29 17.65 0
## 6 0 0 17.13 12.22 0
## 7 0 0 15.22 7.74 0
## 8 0 0 18.96 9.79 0
## 9 0 0 12.87 10.04 0
unmatched <- merge(y = nm, x = r2@data, by = "c2")[, 1]
unmatched
## [1] "DR" "FL" "FR" "GE" "GR" "LI" "OV" "UT" "ZE"
nm[which(nm$c2 %in% unmatched == F), 1:3] # regions that are not matched 1st time
## Vervoerwijzen Totaal.vervoerwijzen Car.d
## 1 Reg aantal aantal
## 10 Noord-Holland 0.5 0.23
## 11 Zuid-Holland 0.47 0.22
## 13 Noord-Brabant 0.49 0.29
duplicated(regs@data$c2) # no duplicates
## logical(0)
nm[, c(1, 29)]
## Vervoerwijzen c2
## 1 Reg RE
## 3 Groningen GR
## 4 Friesland FR
## 5 Drenthe DR
## 6 Overijssel OV
## 7 Flevoland FL
## 8 Gelderland GE
## 9 Utrecht UT
## 10 Noord-Holland NO
## 11 Zuid-Holland ZU
## 12 Zeeland ZE
## 13 Noord-Brabant NO
## 14 Limburg LI
nm[10, 29] # Says ZU, but should be ZH
## [1] "ZU"
nm[10, 29] <- "ZH"
nm[9, 29] # NO but should be NH, North Holland
## [1] "NO"
nm[9, 29] <- "NH"
nm$c2 <- sub("NO", "NB", nm$c2)
nm[, c(1, 29)]
## Vervoerwijzen c2
## 1 Reg RE
## 3 Groningen GR
## 4 Friesland FR
## 5 Drenthe DR
## 6 Overijssel OV
## 7 Flevoland FL
## 8 Gelderland GE
## 9 Utrecht UT
## 10 Noord-Holland NH
## 11 Zuid-Holland ZH
## 12 Zeeland ZE
## 13 Noord-Brabant NB
## 14 Limburg LI
head(nm) # still contains superfluous units
## Vervoerwijzen Totaal.vervoerwijzen Car.d Car.p Train Bus.tram.metro
## 1 Reg aantal aantal aantal aantal aantal
## 3 Groningen 0.46 0.23 0.02 0 0
## 4 Friesland 0.47 0.27 0.03 0 0
## 5 Drenthe 0.52 0.31 0.03 0 0
## 6 Overijssel 0.51 0.27 0.02 0 0
## 7 Flevoland 0.52 0.3 0.02 0 0
## Moto Bicycle Walk Other Totaal.vervoerwijzen.1 Car.d.1 Car.p.1
## 1 aantal aantal aantal aantal km km km
## 3 0 0.15 0.02 0 18.82 27.77 33.8
## 4 0 0.12 0.02 0 17.94 24.56 35.61
## 5 0 0.12 0.02 0 19.81 23.48 39.54
## 6 0 0.15 0.02 0 18.74 25.23 19.49
## 7 0 0.09 0.02 0 24.71 30.39 39.76
## Train.1 Bus.tram.metro.1 Moto.1 Bicycle.1 Walk.1 Other.1
## 1 km km km km km km
## 3 0 0 0 4.05 3.13 0
## 4 0 0 0 3.42 1.94 0
## 5 0 0 0 4.41 2.32 0
## 6 0 0 0 4.28 2 0
## 7 0 0 0 3.67 3.64 0
## Totaal.vervoerwijzen.2 Car.d.2 Car.p.2 Train.2 Bus.tram.metro.2 Moto.2
## 1 minuten minuten minuten minuten minuten minuten
## 3 26.53 29.14 31.81 0 0 0
## 4 23.35 26.33 32.94 0 0 0
## 5 23.82 24.29 35.93 0 0 0
## 6 25.3 28.05 26.6 0 0 0
## 7 33.09 33.25 49.47 0 0 0
## Bicycle.2 Walk.2 Other.2 c2
## 1 minuten minuten minuten RE
## 3 19.29 17.65 0 GR
## 4 13.9 23.55 0 FR
## 5 15.82 11.58 0 DR
## 6 15.22 7.74 0 OV
## 7 13.69 9.38 0 FL
nm <- nm[-1, ] # removes superfluous units
head(nm) # missing times + distances for key modes
## Vervoerwijzen Totaal.vervoerwijzen Car.d Car.p Train Bus.tram.metro Moto
## 3 Groningen 0.46 0.23 0.02 0 0 0
## 4 Friesland 0.47 0.27 0.03 0 0 0
## 5 Drenthe 0.52 0.31 0.03 0 0 0
## 6 Overijssel 0.51 0.27 0.02 0 0 0
## 7 Flevoland 0.52 0.3 0.02 0 0 0
## 8 Gelderland 0.51 0.28 0.02 0 0 0
## Bicycle Walk Other Totaal.vervoerwijzen.1 Car.d.1 Car.p.1 Train.1
## 3 0.15 0.02 0 18.82 27.77 33.8 0
## 4 0.12 0.02 0 17.94 24.56 35.61 0
## 5 0.12 0.02 0 19.81 23.48 39.54 0
## 6 0.15 0.02 0 18.74 25.23 19.49 0
## 7 0.09 0.02 0 24.71 30.39 39.76 0
## 8 0.13 0.03 0 18.63 25.24 25.12 0
## Bus.tram.metro.1 Moto.1 Bicycle.1 Walk.1 Other.1 Totaal.vervoerwijzen.2
## 3 0 0 4.05 3.13 0 26.53
## 4 0 0 3.42 1.94 0 23.35
## 5 0 0 4.41 2.32 0 23.82
## 6 0 0 4.28 2 0 25.3
## 7 0 0 3.67 3.64 0 33.09
## 8 0 0 4.57 1.74 0 26.92
## Car.d.2 Car.p.2 Train.2 Bus.tram.metro.2 Moto.2 Bicycle.2 Walk.2 Other.2
## 3 29.14 31.81 0 0 0 19.29 17.65 0
## 4 26.33 32.94 0 0 0 13.9 23.55 0
## 5 24.29 35.93 0 0 0 15.82 11.58 0
## 6 28.05 26.6 0 0 0 15.22 7.74 0
## 7 33.25 49.47 0 0 0 13.69 9.38 0
## 8 29.33 30.41 0 0 0 18.33 9.14 0
## c2
## 3 GR
## 4 FR
## 5 DR
## 6 OV
## 7 FL
## 8 GE
class(nm$Car.d) # but still factors
## [1] "factor"
for (i in 3:(ncol(nm) - 1)) {
nm[, i] <- as.numeric(as.character(nm[, i]))
}
class(nm$Car.d) # numeric - previous for loop worked
## [1] "numeric"
natdis <- as.matrix(read.csv("NL-Data/2011netherlands.csv", sep = ";")[2, 12:19])
natdis <- as.numeric(natdis) # converts data to numeric
(nm)[, 12:19] # zeros must be replaced by nat. averages
## Car.d.1 Car.p.1 Train.1 Bus.tram.metro.1 Moto.1 Bicycle.1 Walk.1
## 3 27.77 33.80 0 0.00 0.00 4.05 3.13
## 4 24.56 35.61 0 0.00 0.00 3.42 1.94
## 5 23.48 39.54 0 0.00 0.00 4.41 2.32
## 6 25.23 19.49 0 0.00 0.00 4.28 2.00
## 7 30.39 39.76 0 0.00 0.00 3.67 3.64
## 8 25.24 25.12 0 0.00 0.00 4.57 1.74
## 9 24.17 0.00 0 0.00 0.00 5.11 2.32
## 10 24.56 20.91 0 12.10 10.34 4.68 3.10
## 11 22.30 20.64 0 12.69 8.46 4.62 3.07
## 12 23.86 19.28 0 0.00 0.00 3.32 1.46
## 13 22.73 31.70 0 0.00 0.00 4.53 3.52
## 14 20.69 14.34 0 0.00 0.00 4.52 2.29
## Other.1
## 3 0.00
## 4 0.00
## 5 0.00
## 6 0.00
## 7 0.00
## 8 0.00
## 9 0.00
## 10 0.00
## 11 19.09
## 12 0.00
## 13 19.14
## 14 0.00
for (i in 1:8) {
nm[which(nm[, i + 11] == 0), i + 11] <- natdis[i]
}
## Warning: no non-missing arguments to max; returning -Inf
## Warning: no non-missing arguments to max; returning -Inf
## Warning: no non-missing arguments to max; returning -Inf
head(nm)
## Vervoerwijzen Totaal.vervoerwijzen Car.d Car.p Train Bus.tram.metro Moto
## 3 Groningen 0.46 0.23 0.02 0 0 0
## 4 Friesland 0.47 0.27 0.03 0 0 0
## 5 Drenthe 0.52 0.31 0.03 0 0 0
## 6 Overijssel 0.51 0.27 0.02 0 0 0
## 7 Flevoland 0.52 0.30 0.02 0 0 0
## 8 Gelderland 0.51 0.28 0.02 0 0 0
## Bicycle Walk Other Totaal.vervoerwijzen.1 Car.d.1 Car.p.1 Train.1
## 3 0.15 0.02 0 18.82 27.77 33.80 38.35
## 4 0.12 0.02 0 17.94 24.56 35.61 38.35
## 5 0.12 0.02 0 19.81 23.48 39.54 38.35
## 6 0.15 0.02 0 18.74 25.23 19.49 38.35
## 7 0.09 0.02 0 24.71 30.39 39.76 38.35
## 8 0.13 0.03 0 18.63 25.24 25.12 38.35
## Bus.tram.metro.1 Moto.1 Bicycle.1 Walk.1 Other.1 Totaal.vervoerwijzen.2
## 3 13.37 8.75 4.05 3.13 22.59 26.53
## 4 13.37 8.75 3.42 1.94 22.59 23.35
## 5 13.37 8.75 4.41 2.32 22.59 23.82
## 6 13.37 8.75 4.28 2.00 22.59 25.30
## 7 13.37 8.75 3.67 3.64 22.59 33.09
## 8 13.37 8.75 4.57 1.74 22.59 26.92
## Car.d.2 Car.p.2 Train.2 Bus.tram.metro.2 Moto.2 Bicycle.2 Walk.2 Other.2
## 3 29.14 31.81 0 0 0 19.29 17.65 0
## 4 26.33 32.94 0 0 0 13.90 23.55 0
## 5 24.29 35.93 0 0 0 15.82 11.58 0
## 6 28.05 26.60 0 0 0 15.22 7.74 0
## 7 33.25 49.47 0 0 0 13.69 9.38 0
## 8 29.33 30.41 0 0 0 18.33 9.14 0
## c2
## 3 GR
## 4 FR
## 5 DR
## 6 OV
## 7 FL
## 8 GE
# now re-match
`?`(merge # sort = T important to see this default, will result in wrong join if not overridden
)
r2@data <- merge(x = r2@data, y = nm, by = "c2", sort = F) # worked a treat
fr3 <- fortify(r2, region = "c2")
head(fr3)
## long lat order hole piece group id
## 1 6.520 53.19 1 FALSE 1 DR.1 DR
## 2 6.531 53.19 2 FALSE 1 DR.1 DR
## 3 6.548 53.18 3 FALSE 1 DR.1 DR
## 4 6.564 53.16 4 FALSE 1 DR.1 DR
## 5 6.567 53.16 5 FALSE 1 DR.1 DR
## 6 6.572 53.16 6 FALSE 1 DR.1 DR
library(plyr)
names(fr3)[names(fr3) == "id"] <- "c2"
fr3 <- join(x = fr3, y = r2@data)
## Joining by: c2
head(fr3)
## long lat order hole piece group c2 Shape_Leng name code_hasc
## 1 6.520 53.19 1 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 2 6.531 53.19 2 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 3 6.548 53.18 3 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 4 6.564 53.16 4 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 5 6.567 53.16 5 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 6 6.572 53.16 6 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## Vervoerwijzen Totaal.vervoerwijzen Car.d Car.p Train Bus.tram.metro Moto
## 1 Drenthe 0.52 0.31 0.03 0 0 0
## 2 Drenthe 0.52 0.31 0.03 0 0 0
## 3 Drenthe 0.52 0.31 0.03 0 0 0
## 4 Drenthe 0.52 0.31 0.03 0 0 0
## 5 Drenthe 0.52 0.31 0.03 0 0 0
## 6 Drenthe 0.52 0.31 0.03 0 0 0
## Bicycle Walk Other Totaal.vervoerwijzen.1 Car.d.1 Car.p.1 Train.1
## 1 0.12 0.02 0 19.81 23.48 39.54 38.35
## 2 0.12 0.02 0 19.81 23.48 39.54 38.35
## 3 0.12 0.02 0 19.81 23.48 39.54 38.35
## 4 0.12 0.02 0 19.81 23.48 39.54 38.35
## 5 0.12 0.02 0 19.81 23.48 39.54 38.35
## 6 0.12 0.02 0 19.81 23.48 39.54 38.35
## Bus.tram.metro.1 Moto.1 Bicycle.1 Walk.1 Other.1 Totaal.vervoerwijzen.2
## 1 13.37 8.75 4.41 2.32 22.59 23.82
## 2 13.37 8.75 4.41 2.32 22.59 23.82
## 3 13.37 8.75 4.41 2.32 22.59 23.82
## 4 13.37 8.75 4.41 2.32 22.59 23.82
## 5 13.37 8.75 4.41 2.32 22.59 23.82
## 6 13.37 8.75 4.41 2.32 22.59 23.82
## Car.d.2 Car.p.2 Train.2 Bus.tram.metro.2 Moto.2 Bicycle.2 Walk.2 Other.2
## 1 24.29 35.93 0 0 0 15.82 11.58 0
## 2 24.29 35.93 0 0 0 15.82 11.58 0
## 3 24.29 35.93 0 0 0 15.82 11.58 0
## 4 24.29 35.93 0 0 0 15.82 11.58 0
## 5 24.29 35.93 0 0 0 15.82 11.58 0
## 6 24.29 35.93 0 0 0 15.82 11.58 0
p <- ggplot(data = fr3, aes(x = long, y = lat, fill = Car.d))
p + geom_polygon(aes(group = group)) + geom_path(aes(group = group)) + geom_text(data = r2@data,
aes(x = coordinates(r2)[, 1], y = coordinates(r2)[, 2], label = r2$c2))
r2@data
## c2 Shape_Leng name code_hasc Vervoerwijzen
## 1 NB 5.374 Noord-Brabant NL.NB Noord-Brabant
## 2 UT 2.896 Utrecht NL.UT Utrecht
## 3 ZH 4.157 Zuid-Holland NL.ZH Zuid-Holland
## 4 NH 4.488 Noord-Holland NL.NH Noord-Holland
## 5 DR 2.964 Drenthe NL.DR Drenthe
## 6 FR 5.914 Friesland NL.FR Friesland
## 7 GE 5.820 Gelderland NL.GE Gelderland
## 8 GR 3.325 Groningen NL.GR Groningen
## 9 LI 4.515 Limburg NL.LI Limburg
## 10 OV 4.323 Overijssel NL.OV Overijssel
## 11 FL 2.675 Flevoland NL.FL Flevoland
## 12 ZE 5.779 Zeeland NL.ZE Zeeland
## Totaal.vervoerwijzen Car.d Car.p Train Bus.tram.metro Moto Bicycle Walk
## 1 0.49 0.29 0.02 0 0.00 0.00 0.12 0.02
## 2 0.5 0.26 0.00 0 0.00 0.00 0.13 0.02
## 3 0.47 0.22 0.02 0 0.03 0.01 0.12 0.03
## 4 0.5 0.23 0.02 0 0.03 0.01 0.14 0.02
## 5 0.52 0.31 0.03 0 0.00 0.00 0.12 0.02
## 6 0.47 0.27 0.03 0 0.00 0.00 0.12 0.02
## 7 0.51 0.28 0.02 0 0.00 0.00 0.13 0.03
## 8 0.46 0.23 0.02 0 0.00 0.00 0.15 0.02
## 9 0.48 0.30 0.02 0 0.00 0.00 0.09 0.03
## 10 0.51 0.27 0.02 0 0.00 0.00 0.15 0.02
## 11 0.52 0.30 0.02 0 0.00 0.00 0.09 0.02
## 12 0.47 0.28 0.02 0 0.00 0.00 0.12 0.02
## Other Totaal.vervoerwijzen.1 Car.d.1 Car.p.1 Train.1 Bus.tram.metro.1
## 1 0.01 18.43 22.73 31.70 38.35 13.37
## 2 0.00 17.57 24.17 24.97 38.35 13.37
## 3 0.01 16.27 22.30 20.64 38.35 12.69
## 4 0.00 16.77 24.56 20.91 38.35 12.10
## 5 0.00 19.81 23.48 39.54 38.35 13.37
## 6 0.00 17.94 24.56 35.61 38.35 13.37
## 7 0.00 18.63 25.24 25.12 38.35 13.37
## 8 0.00 18.82 27.77 33.80 38.35 13.37
## 9 0.00 16.66 20.69 14.34 38.35 13.37
## 10 0.00 18.74 25.23 19.49 38.35 13.37
## 11 0.00 24.71 30.39 39.76 38.35 13.37
## 12 0.00 17.17 23.86 19.28 38.35 13.37
## Moto.1 Bicycle.1 Walk.1 Other.1 Totaal.vervoerwijzen.2 Car.d.2 Car.p.2
## 1 8.75 4.53 3.52 19.14 25.19 26.34 31.63
## 2 8.75 5.11 2.32 22.59 28.91 31.02 0.00
## 3 8.46 4.62 3.07 19.09 29.10 30.48 29.89
## 4 10.34 4.68 3.10 22.59 30.37 31.88 33.11
## 5 8.75 4.41 2.32 22.59 23.82 24.29 35.93
## 6 8.75 3.42 1.94 22.59 23.35 26.33 32.94
## 7 8.75 4.57 1.74 22.59 26.92 29.33 30.41
## 8 8.75 4.05 3.13 22.59 26.53 29.14 31.81
## 9 8.75 4.52 2.29 22.59 24.63 25.75 20.32
## 10 8.75 4.28 2.00 22.59 25.30 28.05 26.60
## 11 8.75 3.67 3.64 22.59 33.09 33.25 49.47
## 12 8.75 3.32 1.46 22.59 22.92 26.05 39.79
## Train.2 Bus.tram.metro.2 Moto.2 Bicycle.2 Walk.2 Other.2
## 1 0 0.00 0.00 16.57 12.66 23.53
## 2 0 0.00 0.00 18.96 9.79 0.00
## 3 0 43.59 20.94 18.71 15.56 29.11
## 4 0 41.20 22.07 23.69 9.91 0.00
## 5 0 0.00 0.00 15.82 11.58 0.00
## 6 0 0.00 0.00 13.90 23.55 0.00
## 7 0 0.00 0.00 18.33 9.14 0.00
## 8 0 0.00 0.00 19.29 17.65 0.00
## 9 0 0.00 0.00 17.13 12.22 0.00
## 10 0 0.00 0.00 15.22 7.74 0.00
## 11 0 0.00 0.00 13.69 9.38 0.00
## 12 0 0.00 0.00 12.87 10.04 0.00
names(fr3)
## [1] "long" "lat"
## [3] "order" "hole"
## [5] "piece" "group"
## [7] "c2" "Shape_Leng"
## [9] "name" "code_hasc"
## [11] "Vervoerwijzen" "Totaal.vervoerwijzen"
## [13] "Car.d" "Car.p"
## [15] "Train" "Bus.tram.metro"
## [17] "Moto" "Bicycle"
## [19] "Walk" "Other"
## [21] "Totaal.vervoerwijzen.1" "Car.d.1"
## [23] "Car.p.1" "Train.1"
## [25] "Bus.tram.metro.1" "Moto.1"
## [27] "Bicycle.1" "Walk.1"
## [29] "Other.1" "Totaal.vervoerwijzen.2"
## [31] "Car.d.2" "Car.p.2"
## [33] "Train.2" "Bus.tram.metro.2"
## [35] "Moto.2" "Bicycle.2"
## [37] "Walk.2" "Other.2"
ec <- c(3, 0, 0.77, 0.57, 1.7, 0.09, 0.13, 0) # Energy costs of transport modes, in order
names(ec) <- names(fr3[, 14:21])
ec
## Car.p Train Bus.tram.metro
## 3.00 0.00 0.77
## Moto Bicycle Walk
## 0.57 1.70 0.09
## Other Totaal.vervoerwijzen.1
## 0.13 0.00
r3 <- r2 # new object, to add energy costs to (keep original r2, as backup)
names(r3@data)
## [1] "c2" "Shape_Leng"
## [3] "name" "code_hasc"
## [5] "Vervoerwijzen" "Totaal.vervoerwijzen"
## [7] "Car.d" "Car.p"
## [9] "Train" "Bus.tram.metro"
## [11] "Moto" "Bicycle"
## [13] "Walk" "Other"
## [15] "Totaal.vervoerwijzen.1" "Car.d.1"
## [17] "Car.p.1" "Train.1"
## [19] "Bus.tram.metro.1" "Moto.1"
## [21] "Bicycle.1" "Walk.1"
## [23] "Other.1" "Totaal.vervoerwijzen.2"
## [25] "Car.d.2" "Car.p.2"
## [27] "Train.2" "Bus.tram.metro.2"
## [29] "Moto.2" "Bicycle.2"
## [31] "Walk.2" "Other.2"
# r3@data[,7:14] <- (r3@data[,7:14]) * 2 Originally used this as an
# approximation - multiply by 2
`?`(sweep # check how this function works
)
r3$Totaal.vervoerwijzen <- as.numeric(as.character(r3$Totaal.vervoerwijzen))
summary(1/r3$Totaal.vervoerwijzen) # Shows that 2 is a good estimate, but out by an average of 3.7%
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.92 1.96 2.02 2.04 2.13 2.17
r3@data[, 7:14] <- sweep(r3@data[, 7:14], MARGIN = 1, STATS = r3$Totaal.vervoerwijzen,
FUN = "/") # true proportions
ecosts <- r3@data[, 7:14] # set-up correctly dimensioned df
for (i in 1:nrow(r3@data)) {
ecosts[i, ] <- r3@data[i, 7:14] * r3@data[i, 16:23] * ec
}
head(r3@data)
## c2 Shape_Leng name code_hasc Vervoerwijzen Totaal.vervoerwijzen
## 1 NB 5.374 Noord-Brabant NL.NB Noord-Brabant 0.49
## 2 UT 2.896 Utrecht NL.UT Utrecht 0.50
## 3 ZH 4.157 Zuid-Holland NL.ZH Zuid-Holland 0.47
## 4 NH 4.488 Noord-Holland NL.NH Noord-Holland 0.50
## 5 DR 2.964 Drenthe NL.DR Drenthe 0.52
## 6 FR 5.914 Friesland NL.FR Friesland 0.47
## Car.d Car.p Train Bus.tram.metro Moto Bicycle Walk Other
## 1 0.5918 0.04082 0 0.00000 0.00000 0.2449 0.04082 0.02041
## 2 0.5200 0.00000 0 0.00000 0.00000 0.2600 0.04000 0.00000
## 3 0.4681 0.04255 0 0.06383 0.02128 0.2553 0.06383 0.02128
## 4 0.4600 0.04000 0 0.06000 0.02000 0.2800 0.04000 0.00000
## 5 0.5962 0.05769 0 0.00000 0.00000 0.2308 0.03846 0.00000
## 6 0.5745 0.06383 0 0.00000 0.00000 0.2553 0.04255 0.00000
## Totaal.vervoerwijzen.1 Car.d.1 Car.p.1 Train.1 Bus.tram.metro.1 Moto.1
## 1 18.43 22.73 31.70 38.35 13.37 8.75
## 2 17.57 24.17 24.97 38.35 13.37 8.75
## 3 16.27 22.30 20.64 38.35 12.69 8.46
## 4 16.77 24.56 20.91 38.35 12.10 10.34
## 5 19.81 23.48 39.54 38.35 13.37 8.75
## 6 17.94 24.56 35.61 38.35 13.37 8.75
## Bicycle.1 Walk.1 Other.1 Totaal.vervoerwijzen.2 Car.d.2 Car.p.2 Train.2
## 1 4.53 3.52 19.14 25.19 26.34 31.63 0
## 2 5.11 2.32 22.59 28.91 31.02 0.00 0
## 3 4.62 3.07 19.09 29.10 30.48 29.89 0
## 4 4.68 3.10 22.59 30.37 31.88 33.11 0
## 5 4.41 2.32 22.59 23.82 24.29 35.93 0
## 6 3.42 1.94 22.59 23.35 26.33 32.94 0
## Bus.tram.metro.2 Moto.2 Bicycle.2 Walk.2 Other.2
## 1 0.00 0.00 16.57 12.66 23.53
## 2 0.00 0.00 18.96 9.79 0.00
## 3 43.59 20.94 18.71 15.56 29.11
## 4 41.20 22.07 23.69 9.91 0.00
## 5 0.00 0.00 15.82 11.58 0.00
## 6 0.00 0.00 13.90 23.55 0.00
r3@data$etot <- rowSums(ecosts)
r3 <- spTransform(r3, CRS("+init=epsg:27700"))
r3$id <- 1:length(r3$name)
fr3 <- fortify(r3, region = "c2")
head(fr3)
## long lat order hole piece group id
## 1 968762 399879 1 FALSE 1 DR.1 DR
## 2 969477 400058 2 FALSE 1 DR.1 DR
## 3 970799 398641 3 FALSE 1 DR.1 DR
## 4 972115 396858 4 FALSE 1 DR.1 DR
## 5 972343 396705 5 FALSE 1 DR.1 DR
## 6 972720 396617 6 FALSE 1 DR.1 DR
names(fr3)[7] <- "c2"
fr3 <- join(x = fr3, y = r3@data, by = "c2")
head(fr3)
## long lat order hole piece group c2 Shape_Leng name code_hasc
## 1 968762 399879 1 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 2 969477 400058 2 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 3 970799 398641 3 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 4 972115 396858 4 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 5 972343 396705 5 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 6 972720 396617 6 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## Vervoerwijzen Totaal.vervoerwijzen Car.d Car.p Train Bus.tram.metro
## 1 Drenthe 0.52 0.5962 0.05769 0 0
## 2 Drenthe 0.52 0.5962 0.05769 0 0
## 3 Drenthe 0.52 0.5962 0.05769 0 0
## 4 Drenthe 0.52 0.5962 0.05769 0 0
## 5 Drenthe 0.52 0.5962 0.05769 0 0
## 6 Drenthe 0.52 0.5962 0.05769 0 0
## Moto Bicycle Walk Other Totaal.vervoerwijzen.1 Car.d.1 Car.p.1
## 1 0 0.2308 0.03846 0 19.81 23.48 39.54
## 2 0 0.2308 0.03846 0 19.81 23.48 39.54
## 3 0 0.2308 0.03846 0 19.81 23.48 39.54
## 4 0 0.2308 0.03846 0 19.81 23.48 39.54
## 5 0 0.2308 0.03846 0 19.81 23.48 39.54
## 6 0 0.2308 0.03846 0 19.81 23.48 39.54
## Train.1 Bus.tram.metro.1 Moto.1 Bicycle.1 Walk.1 Other.1
## 1 38.35 13.37 8.75 4.41 2.32 22.59
## 2 38.35 13.37 8.75 4.41 2.32 22.59
## 3 38.35 13.37 8.75 4.41 2.32 22.59
## 4 38.35 13.37 8.75 4.41 2.32 22.59
## 5 38.35 13.37 8.75 4.41 2.32 22.59
## 6 38.35 13.37 8.75 4.41 2.32 22.59
## Totaal.vervoerwijzen.2 Car.d.2 Car.p.2 Train.2 Bus.tram.metro.2 Moto.2
## 1 23.82 24.29 35.93 0 0 0
## 2 23.82 24.29 35.93 0 0 0
## 3 23.82 24.29 35.93 0 0 0
## 4 23.82 24.29 35.93 0 0 0
## 5 23.82 24.29 35.93 0 0 0
## 6 23.82 24.29 35.93 0 0 0
## Bicycle.2 Walk.2 Other.2 etot id
## 1 15.82 11.58 0 42.1 5
## 2 15.82 11.58 0 42.1 5
## 3 15.82 11.58 0 42.1 5
## 4 15.82 11.58 0 42.1 5
## 5 15.82 11.58 0 42.1 5
## 6 15.82 11.58 0 42.1 5
fr3$lat <- fr3$lat/1000
fr3$long <- fr3$long/1000
head(fr3)
## long lat order hole piece group c2 Shape_Leng name code_hasc
## 1 968.8 399.9 1 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 2 969.5 400.1 2 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 3 970.8 398.6 3 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 4 972.1 396.9 4 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 5 972.3 396.7 5 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## 6 972.7 396.6 6 FALSE 1 DR.1 DR 2.964 Drenthe NL.DR
## Vervoerwijzen Totaal.vervoerwijzen Car.d Car.p Train Bus.tram.metro
## 1 Drenthe 0.52 0.5962 0.05769 0 0
## 2 Drenthe 0.52 0.5962 0.05769 0 0
## 3 Drenthe 0.52 0.5962 0.05769 0 0
## 4 Drenthe 0.52 0.5962 0.05769 0 0
## 5 Drenthe 0.52 0.5962 0.05769 0 0
## 6 Drenthe 0.52 0.5962 0.05769 0 0
## Moto Bicycle Walk Other Totaal.vervoerwijzen.1 Car.d.1 Car.p.1
## 1 0 0.2308 0.03846 0 19.81 23.48 39.54
## 2 0 0.2308 0.03846 0 19.81 23.48 39.54
## 3 0 0.2308 0.03846 0 19.81 23.48 39.54
## 4 0 0.2308 0.03846 0 19.81 23.48 39.54
## 5 0 0.2308 0.03846 0 19.81 23.48 39.54
## 6 0 0.2308 0.03846 0 19.81 23.48 39.54
## Train.1 Bus.tram.metro.1 Moto.1 Bicycle.1 Walk.1 Other.1
## 1 38.35 13.37 8.75 4.41 2.32 22.59
## 2 38.35 13.37 8.75 4.41 2.32 22.59
## 3 38.35 13.37 8.75 4.41 2.32 22.59
## 4 38.35 13.37 8.75 4.41 2.32 22.59
## 5 38.35 13.37 8.75 4.41 2.32 22.59
## 6 38.35 13.37 8.75 4.41 2.32 22.59
## Totaal.vervoerwijzen.2 Car.d.2 Car.p.2 Train.2 Bus.tram.metro.2 Moto.2
## 1 23.82 24.29 35.93 0 0 0
## 2 23.82 24.29 35.93 0 0 0
## 3 23.82 24.29 35.93 0 0 0
## 4 23.82 24.29 35.93 0 0 0
## 5 23.82 24.29 35.93 0 0 0
## 6 23.82 24.29 35.93 0 0 0
## Bicycle.2 Walk.2 Other.2 etot id
## 1 15.82 11.58 0 42.1 5
## 2 15.82 11.58 0 42.1 5
## 3 15.82 11.58 0 42.1 5
## 4 15.82 11.58 0 42.1 5
## 5 15.82 11.58 0 42.1 5
## 6 15.82 11.58 0 42.1 5
# if analysis alread done... load('.RData')
p <- ggplot(data = fr3, aes(x = long, y = lat))
p + geom_polygon(aes(group = group, fill = etot)) + geom_path(aes(group = group)) +
geom_text(data = r3@data, aes(x = coordinates(r3)[, 1]/1000, y = coordinates(r3)[,
2]/1000, label = r3$c2), color = "blue") + scale_fill_continuous(low = "green",
high = "red", name = "Etrp (MJ)", limits = c(20, 55)) + coord_fixed() +
xlab("Easting (km)") + ylab("Northing (km)") #+ theme_minimal()
