Module 11 Exercise
Lucas Brizolara
2022-06-14
Data Manipulation
For this assingment, we utilized the data.table package in order to do more advanced data manipulation. This is similar to utilizing dplyr package. This package however, is much better at working with larger data sets.
It is important to load the packages in and load the data. Which we did.
setwd("~/Desktop/GEOG5680/module11")
list.files()## [1] "flights14.csv" "iris.csv"
## [3] "Module 11 Exercise Knit.Rmd" "Module 11 Exercise.R"
## [5] "Module 11 Notes.R" "Module-11-Exercise-Knit.Rmd"
## [7] "Temperature.csv"library(data.table)- Question 1: Read in the data using fread
ftemp <- fread("Temperature.csv")
ftemp## Sample Date DateNr dDay1 dDay2 dDay3 Station Area
## 1: DANT.19900110 19900110 10/1/90 7 9 9 DANT WZ
## 2: DANT.19900206 19900206 6/2/90 34 36 36 DANT WZ
## 3: DANT.19900308 19900308 8/3/90 64 66 66 DANT WZ
## 4: DANT.19900404 19900404 4/4/90 91 93 93 DANT WZ
## 5: DANT.19900509 19900509 9/5/90 126 128 128 DANT WZ
## ---
## 8524: ZUID.20050926 20050926 9/26/2005 5745 5747 268 ZUID WZ
## 8525: ZUID.20051012 20051012 12/10/05 5761 5763 284 ZUID WZ
## 8526: ZUID.20051027 20051027 10/27/2005 5776 5778 299 ZUID WZ
## 8527: ZUID.20051110 20051110 10/11/05 5790 5792 313 ZUID WZ
## 8528: ZUID.20051212 20051212 12/12/05 5822 5824 345 ZUID WZ
## 31UE_ED50 31UN_ED50 Year Month Season Salinity Temperature CHLFa
## 1: 681379.6 5920571 1990 1 winter 29.19 4.00 1.30
## 2: 681379.6 5920571 1990 2 winter 27.37 6.00 NA
## 3: 681379.6 5920571 1990 3 spring 24.99 7.30 21.10
## 4: 681379.6 5920571 1990 4 spring 28.79 8.20 25.00
## 5: 681379.6 5920571 1990 5 spring 33.28 17.40 10.20
## ---
## 8524: 733386.3 5928197 2005 9 autumn 30.91 15.47 11.40
## 8525: 733386.3 5928197 2005 10 autumn 31.18 13.45 8.30
## 8526: 733386.3 5928197 2005 10 autumn 28.67 12.09 4.56
## 8527: 733386.3 5928197 2005 11 autumn 29.53 9.03 4.94
## 8528: 733386.3 5928197 2005 12 winter 29.08 5.13 2.38- Question 2: Extract all winter observations
winter <- ftemp[Season == "winter"]
head(winter)## Sample Date DateNr dDay1 dDay2 dDay3 Station Area 31UE_ED50
## 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
## 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- Question 3: Extract all winter observations
winter.nc <- ftemp[Season == "winter" & Area == "NC"]
winter.nc## Sample Date DateNr dDay1 dDay2 dDay3 Station Area 31UE_ED50
## 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
## ---
## 177: T235.20040209 20040209 9/2/04 5150 5152 39 T235 NC 510032.3
## 178: T235.20041214 20041214 12/14/2004 5459 5461 348 T235 NC 510032.3
## 179: T235.20050126 20050126 1/26/2005 5502 5504 25 T235 NC 510032.3
## 180: T235.20050214 20050214 2/14/2005 5521 5523 44 T235 NC 510032.3
## 181: T235.20051220 20051220 12/20/2005 5830 5832 353 T235 NC 510032.3
## 31UN_ED50 Year Month Season Salinity Temperature CHLFa
## 1: 6001110 1990 1 winter 34.82 8.50 0.30
## 2: 6001110 1990 2 winter NA NA NA
## 3: 6001110 1990 12 winter 34.80 9.20 0.40
## 4: 6001110 1991 1 winter 34.86 6.10 0.68
## 5: 6001110 1991 2 winter 34.53 5.20 0.34
## ---
## 177: 6114101 2004 2 winter NA NA NA
## 178: 6114101 2004 12 winter 34.96 8.47 0.62
## 179: 6114101 2005 1 winter 35.09 6.44 0.62
## 180: 6114101 2005 2 winter NA NA NA
## 181: 6114101 2005 12 winter 33.87 8.19 1.12- Question 4: Select only the columns Area, Season, Temperature
select_cols = c("Area", "Season", "Temperature")
ftemp_ast <- ftemp[, ..select_cols]
ftemp_ast## Area Season Temperature
## 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- Questions 5: Select only the columns Area and Temperature but only for winter observations
select_colsW = c("Area", "Temperature")
ftempt_atW <- ftemp[Season == "winter", ..select_colsW]
ftempt_atW## Area Temperature
## 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- Question 6: Find the total number of observations in winter
ftemp[Season == "winter", .N]## [1] 1706- Question 7: Calculate the mean temperature and mean salinity in winter.
fwin_tsal <- ftemp[Season == "winter", .(mean(Temperature, na.rm = TRUE),
mean(Salinity, na.rm = TRUE))]
fwin_tsal## V1 V2
## 1: 5.57162 29.15756- Question 8: Find the number of observations per station in winter.
winsta <- ftemp[Season == "winter", .N, by = .(Station)]
winsta## Station N
## 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- Question 9: Find the number of observations per station per season
seasta <- ftemp[, .N, by = .(Station, Season)]
seasta## Station Season N
## 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- Question 10: Estimate average temperatures by month
avtemp <- ftemp[, .(mean(Temperature, na.rm = TRUE)),
by = .(Month)]
avtemp## Month V1
## 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- Question 11: Estimate average temperatures by month by area.
avarea <- ftemp[, .(mean(Temperature, na.rm = TRUE)),
by = .(Month, Area)]
avarea## Month Area V1
## 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- Question 12: Plot the output of the previous question using ggplot2 using the geom_line() geometry
library(ggplot2)
ggplot(avarea, aes(x = Month, y = V1, col = Area)) + geom_line() 
- That graph draining me of life.