library(data.table)
library(ggplot2)GEOG 5680/6680 Module 11: Data Manipulation III
Setup
Read In The Data Using fread
# This first tries to read Temperature.csv from the same folder as this
# Quarto file. If it is not there, it uses the original file location.
data_file <- "Temperature.csv"
if (!file.exists(data_file)) {
data_file <- "C:/Users/yolom/OneDrive/Desktop/GEOG5680/Module 11/Temperature.csv"
}
temperature <- fread(data_file)
dim(temperature)[1] 8528 16names(temperature) [1] "Sample" "Date" "DateNr" "dDay1" "dDay2"
[6] "dDay3" "Station" "Area" "31UE_ED50" "31UN_ED50"
[11] "Year" "Month" "Season" "Salinity" "Temperature"
[16] "CHLFa" head(temperature) 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.19900308 19900308 8/3/90 64 66 66 DANT WZ 681379.6
4: DANT.19900404 19900404 4/4/90 91 93 93 DANT WZ 681379.6
5: DANT.19900509 19900509 9/5/90 126 128 128 DANT WZ 681379.6
6: DANT.19900620 19900620 6/20/1990 168 170 170 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 1.3
2: 5920571 1990 2 winter 27.37 6.0 NA
3: 5920571 1990 3 spring 24.99 7.3 21.1
4: 5920571 1990 4 spring 28.79 8.2 25.0
5: 5920571 1990 5 spring 33.28 17.4 10.2
6: 5920571 1990 6 summer 32.69 18.1 6.21. Extract All Winter Observations
winter_observations <- temperature[Season == "winter"]
winter_observations Sample Date DateNr dDay1 dDay2 dDay3 Station Area
<char> <int> <char> <int> <int> <int> <char> <char>
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.19901212 19901212 12/12/90 343 345 345 DANT WZ
4: DANT.19910116 19910116 1/16/1991 378 380 15 DANT WZ
5: DANT.19910226 19910226 2/26/1991 419 421 56 DANT WZ
---
1702: ZUID.20040216 20040216 2/16/2004 5157 5159 46 ZUID WZ
1703: ZUID.20041208 20041208 8/12/04 5453 5455 342 ZUID WZ
1704: ZUID.20050119 20050119 1/19/2005 5495 5497 18 ZUID WZ
1705: ZUID.20050218 20050218 2/18/2005 5525 5527 48 ZUID WZ
1706: ZUID.20051212 20051212 12/12/05 5822 5824 345 ZUID WZ
31UE_ED50 31UN_ED50 Year Month Season Salinity Temperature CHLFa
<num> <num> <int> <int> <char> <num> <num> <num>
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 12 winter 31.50 4.20 60.50
4: 681379.6 5920571 1991 1 winter 20.83 -0.30 2.30
5: 681379.6 5920571 1991 2 winter 28.06 3.90 3.52
---
1702: 733386.3 5928197 2004 2 winter 24.70 4.40 NA
1703: 733386.3 5928197 2004 12 winter 28.67 4.72 1.52
1704: 733386.3 5928197 2005 1 winter 28.39 3.57 4.12
1705: 733386.3 5928197 2005 2 winter 29.31 1.31 6.56
1706: 733386.3 5928197 2005 12 winter 29.08 5.13 2.382. Extract All Winter Observations For Zone NC
winter_nc <- temperature[Season == "winter" & Area == "NC"]
winter_nc Sample Date DateNr dDay1 dDay2 dDay3 Station Area
<char> <int> <char> <int> <int> <int> <char> <char>
1: T100.19900103 19900103 3/1/90 0 2 2 T100 NC
2: T100.19900205 19900205 5/2/90 33 35 35 T100 NC
3: T100.19901218 19901218 12/18/1990 349 351 351 T100 NC
4: T100.19910116 19910116 1/16/1991 378 380 15 T100 NC
5: T100.19910205 19910205 5/2/91 398 400 35 T100 NC
---
177: T235.20040209 20040209 9/2/04 5150 5152 39 T235 NC
178: T235.20041214 20041214 12/14/2004 5459 5461 348 T235 NC
179: T235.20050126 20050126 1/26/2005 5502 5504 25 T235 NC
180: T235.20050214 20050214 2/14/2005 5521 5523 44 T235 NC
181: T235.20051220 20051220 12/20/2005 5830 5832 353 T235 NC
31UE_ED50 31UN_ED50 Year Month Season Salinity Temperature CHLFa
<num> <num> <int> <int> <char> <num> <num> <num>
1: 587650.2 6001110 1990 1 winter 34.82 8.50 0.30
2: 587650.2 6001110 1990 2 winter NA NA NA
3: 587650.2 6001110 1990 12 winter 34.80 9.20 0.40
4: 587650.2 6001110 1991 1 winter 34.86 6.10 0.68
5: 587650.2 6001110 1991 2 winter 34.53 5.20 0.34
---
177: 510032.3 6114101 2004 2 winter NA NA NA
178: 510032.3 6114101 2004 12 winter 34.96 8.47 0.62
179: 510032.3 6114101 2005 1 winter 35.09 6.44 0.62
180: 510032.3 6114101 2005 2 winter NA NA NA
181: 510032.3 6114101 2005 12 winter 33.87 8.19 1.123. Select Only Area, Season, And Temperature
area_season_temperature <- temperature[, .(Area, Season, Temperature)]
area_season_temperature 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 5.134. Select Area And Temperature For Winter Observations
winter_area_temperature <- temperature[
Season == "winter",
.(Area, Temperature)
]
winter_area_temperature 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 5.135. Total Number Of Observations In Winter
n_winter <- temperature[Season == "winter", .N]
n_winter[1] 17066. Mean Temperature And Mean Salinity In Winter
winter_means <- temperature[
Season == "winter",
.(
mean_temperature = mean(Temperature, na.rm = TRUE),
mean_salinity = mean(Salinity, na.rm = TRUE)
)
]
winter_means mean_temperature mean_salinity
<num> <num>
1: 5.57162 29.157567. Number Of Observations Per Station In Winter
winter_station_counts <- temperature[
Season == "winter",
.N,
keyby = Station
]
winter_station_countsKey: <Station>
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
<char> <int>8. Number Of Observations Per Station Per Season
station_season_counts <- temperature[
,
.N,
keyby = .(Station, Season)
]
station_season_countsKey: <Station, Season>
Station Season N
<char> <char> <int>
1: DANT autumn 72
2: DANT spring 89
3: DANT summer 89
4: DANT winter 50
5: DREI autumn 61
---
114: ZIJP winter 54
115: ZUID autumn 73
116: ZUID spring 89
117: ZUID summer 89
118: ZUID winter 529. Average Temperatures By Month
average_temperature_month <- temperature[
,
.(mean_temperature = mean(Temperature, na.rm = TRUE)),
keyby = Month
]
average_temperature_monthKey: <Month>
Month mean_temperature
<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 6.74633910. Average Temperatures By Month By Area
average_temperature_month_area <- temperature[
,
.(mean_temperature = mean(Temperature, na.rm = TRUE)),
keyby = .(Area, Month)
]
average_temperature_month_areaKey: <Area, Month>
Area Month mean_temperature
<char> <int> <num>
1: ED 1 3.086333
2: ED 2 3.306667
3: ED 3 5.648000
4: ED 4 9.470000
5: ED 5 14.025161
---
116: WZ 8 19.548851
117: WZ 9 15.905122
118: WZ 10 12.288816
119: WZ 11 8.261600
120: WZ 12 4.98511111. Plot Average Temperatures By Month By Area
ggplot(
average_temperature_month_area,
aes(x = Month, y = mean_temperature, color = Area)
) +
geom_line(linewidth = 1) +
geom_point(size = 1.5) +
scale_x_continuous(breaks = 1:12) +
labs(
title = "Average Sea Temperature By Month And Area",
x = "Month",
y = "Average temperature (C)",
color = "Area"
) +
theme_minimal()