Read in the data using fread
library(data.table)
library(ggplot2)
library(magrittr)
temp = fread("Temperature.csv")
Extract all winter observations
winterTemp = temp[Season == "winter"]
head(winterTemp)
## Sample Date DateNr dDay1 dDay2 dDay3 Station Area 31UE_ED50
## <char> <int> <char> <int> <int> <int> <char> <char> <num>
## 1: DANT.19900110 19900110 10/1/90 7 9 9 DANT WZ 681379.6
## 2: DANT.19900206 19900206 6/2/90 34 36 36 DANT WZ 681379.6
## 3: DANT.19901212 19901212 12/12/90 343 345 345 DANT WZ 681379.6
## 4: DANT.19910116 19910116 1/16/1991 378 380 15 DANT WZ 681379.6
## 5: DANT.19910226 19910226 2/26/1991 419 421 56 DANT WZ 681379.6
## 6: DANT.19911219 19911219 12/19/1991 715 717 352 DANT WZ 681379.6
## 31UN_ED50 Year Month Season Salinity Temperature CHLFa
## <num> <int> <int> <char> <num> <num> <num>
## 1: 5920571 1990 1 winter 29.19 4.0 1.30
## 2: 5920571 1990 2 winter 27.37 6.0 NA
## 3: 5920571 1990 12 winter 31.50 4.2 60.50
## 4: 5920571 1991 1 winter 20.83 -0.3 2.30
## 5: 5920571 1991 2 winter 28.06 3.9 3.52
## 6: 5920571 1991 12 winter 25.31 3.9 3.50
Extract all winter observations for zone NC
winterNC = temp[Season == "winter" & Area == "NC"]
head(winterNC)
## Sample Date DateNr dDay1 dDay2 dDay3 Station Area 31UE_ED50
## <char> <int> <char> <int> <int> <int> <char> <char> <num>
## 1: T100.19900103 19900103 3/1/90 0 2 2 T100 NC 587650.2
## 2: T100.19900205 19900205 5/2/90 33 35 35 T100 NC 587650.2
## 3: T100.19901218 19901218 12/18/1990 349 351 351 T100 NC 587650.2
## 4: T100.19910116 19910116 1/16/1991 378 380 15 T100 NC 587650.2
## 5: T100.19910205 19910205 5/2/91 398 400 35 T100 NC 587650.2
## 6: T100.19911211 19911211 11/12/91 707 709 344 T100 NC 587650.2
## 31UN_ED50 Year Month Season Salinity Temperature CHLFa
## <num> <int> <int> <char> <num> <num> <num>
## 1: 6001110 1990 1 winter 34.82 8.5 0.30
## 2: 6001110 1990 2 winter NA NA NA
## 3: 6001110 1990 12 winter 34.80 9.2 0.40
## 4: 6001110 1991 1 winter 34.86 6.1 0.68
## 5: 6001110 1991 2 winter 34.53 5.2 0.34
## 6: 6001110 1991 12 winter 34.79 9.7 0.44
Select only the columns “Area”, “Season” and “Temperature”
AreaSeasTemp = temp[, .(Area, Season, Temperature)]
AreaSeasTemp
## Area Season Temperature
## <char> <char> <num>
## 1: WZ winter 4.00
## 2: WZ winter 6.00
## 3: WZ spring 7.30
## 4: WZ spring 8.20
## 5: WZ spring 17.40
## ---
## 8524: WZ autumn 15.47
## 8525: WZ autumn 13.45
## 8526: WZ autumn 12.09
## 8527: WZ autumn 9.03
## 8528: WZ winter 5.13
Select only the columns “Area” and “Temperature” but only for winter observations
winterAreaTemp = temp[Season == "winter", .(Area, Temperature)]
winterAreaTemp
## Area Temperature
## <char> <num>
## 1: WZ 4.00
## 2: WZ 6.00
## 3: WZ 4.20
## 4: WZ -0.30
## 5: WZ 3.90
## ---
## 1702: WZ 4.40
## 1703: WZ 4.72
## 1704: WZ 3.57
## 1705: WZ 1.31
## 1706: WZ 5.13
Find the total number of observations in winter
winterObs = temp[Season == "winter", .N]
winterObs
## [1] 1706
Calculate the mean temperature and mean salinity in winter
winterMean = temp[Season == "winter",
.(m_temp = mean(Temperature, na.rm = TRUE), m_salinity = mean(Salinity, na.rm = TRUE))]
winterMean
## m_temp m_salinity
## <num> <num>
## 1: 5.57162 29.15756
Find the number of observations per station in winter
stationWinter = temp[Season == "winter", .N, by = Station]
stationWinter
## Station N
## <char> <int>
## 1: DANT 50
## 2: DREI 52
## 3: G6 101
## 4: GROO 50
## 5: HAMM 55
## 6: HANS 56
## 7: HUIB 50
## 8: LODS 54
## 9: MARS 49
## 10: N02 115
## 11: N10 131
## 12: N20 50
## 13: N70 50
## 14: R03 32
## 15: SOEL 50
## 16: T004 97
## 17: T010 45
## 18: T100 45
## 19: T135 46
## 20: T175 45
## 21: T235 45
## 22: VLIS 84
## 23: W02 99
## 24: W20 47
## 25: W70 47
## 26: WISS 55
## 27: ZIJP 54
## 28: ZUID 52
## Station N
Find the number of observations per station per season
stationSeason = temp[, .N, by = .(Station, Season)]
stationSeason
## Station Season N
## <char> <char> <int>
## 1: DANT winter 50
## 2: DANT spring 89
## 3: DANT summer 89
## 4: DANT autumn 72
## 5: DREI winter 52
## ---
## 114: ZIJP autumn 61
## 115: ZUID winter 52
## 116: ZUID spring 89
## 117: ZUID summer 89
## 118: ZUID autumn 73
Estimate average temperatures by month
avgTempMonth = temp[,.(m_temp = mean(Temperature, na.rm = TRUE)), by = .(Month)]
avgTempMonth
## Month m_temp
## <int> <num>
## 1: 1 5.174210
## 2: 2 4.737400
## 3: 3 6.125961
## 4: 4 8.702035
## 5: 5 12.293479
## 6: 6 15.659933
## 7: 7 18.077343
## 8: 8 19.388355
## 9: 9 16.995974
## 10: 10 13.619670
## 11: 11 9.848891
## 12: 12 6.746339
Estimate average temperatures by month by area
avgTempMonthArea = temp[,.(m_temp = mean(Temperature, na.rm = TRUE)), by = .(Month, Area)]
avgTempMonthArea
## Month Area m_temp
## <int> <char> <num>
## 1: 1 WZ 3.377826
## 2: 2 WZ 3.925800
## 3: 3 WZ 5.818481
## 4: 4 WZ 9.270805
## 5: 5 WZ 13.398191
## ---
## 116: 1 NC 6.789808
## 117: 2 NC 5.682581
## 118: 3 NC 5.837500
## 119: 11 NC 10.978269
## 120: 12 NC 8.716957
Plot the output of the previous question using ggplot2 using the geom_line() geometry
ggplot(avgTempMonthArea, aes(x = Month, y = m_temp, col = Area)) + geom_line()