Temp <- read.csv ("Temperature.csv")Exercise04
Exercise 4
Read in the temperature data
Now find the mean and standard deviation of the salinity and the temperature
mean(Temp$Salinity, na.rm = TRUE)[1] 29.70221sd(Temp$Salinity, na.rm = TRUE)[1] 5.421593mean(Temp$Temperature, na.rm = TRUE)[1] 12.20743sd(Temp$Temperature, na.rm = TRUE)[1] 5.412521Use tapply() to find the average values of temperature and salinity by year and by station
tapply(Temp$Temperature, Temp$Station, mean, na.rm = TRUE) DANT DREI G6 GROO HAMM HANS HUIB LODS
12.05908 12.77160 10.66570 12.25853 12.50000 13.54894 11.85353 12.61192
MARS N02 N10 N20 N70 R03 R50 R70
12.39607 11.37433 12.45878 12.19753 12.14789 12.80000 13.94911 13.98022
SOEL T004 T010 T100 T135 T175 T235 VLIS
13.21203 11.28425 12.37517 11.94766 11.75512 11.55431 11.32355 12.79292
W02 W20 W70 WISS ZIJP ZUID
10.51829 11.87937 12.18243 12.45090 12.55904 11.83928 tapply(Temp$Salinity, Temp$Station, mean, na.rm = TRUE) DANT DREI G6 GROO HAMM HANS HUIB LODS
28.94468 29.83813 30.59610 14.57571 31.35738 18.29124 29.52631 30.73000
MARS N02 N10 N20 N70 R03 R50 R70
28.03457 28.78695 30.45223 31.93275 34.94147 30.54978 33.49888 33.67944
SOEL T004 T010 T100 T135 T175 T235 VLIS
18.09477 32.08114 32.72095 34.56746 34.67667 34.75135 34.87812 29.55476
W02 W20 W70 WISS ZIJP ZUID
32.05992 33.31554 35.02006 31.75164 29.39230 28.83997 tapply(Temp$Temperature, Temp$Station, sd, na.rm = TRUE) DANT DREI G6 GROO HAMM HANS HUIB LODS
5.987803 6.175500 5.188964 6.325493 5.671482 5.721610 5.823096 6.031458
MARS N02 N10 N20 N70 R03 R50 R70
5.341018 5.361139 5.054397 4.992858 4.118523 5.611473 4.077805 4.216925
SOEL T004 T010 T100 T135 T175 T235 VLIS
6.089879 5.408686 4.976624 4.473144 4.410690 4.381121 4.180605 5.492237
W02 W20 W70 WISS ZIJP ZUID
5.394560 4.960567 3.814414 5.516071 5.847359 5.981059 tapply(Temp$Salinity, Temp$Station, sd, na.rm = TRUE) DANT DREI G6 GROO HAMM HANS HUIB LODS
3.4602295 1.3371179 1.5164455 5.2725882 1.0500410 4.3378055 2.2572583 1.1367087
MARS N02 N10 N20 N70 R03 R50 R70
3.2969221 2.1095210 1.4870491 1.1096109 0.3399558 1.6110321 0.6010265 0.8790095
SOEL T004 T010 T100 T135 T175 T235 VLIS
4.2692405 1.0343277 0.9278039 0.2762276 0.1908589 0.1870987 0.1700748 2.1790708
W02 W20 W70 WISS ZIJP ZUID
1.0503075 0.8222336 0.2762382 1.0824899 1.2524431 2.8814232 tapply(Temp$Temperature, Temp$Year, mean, na.rm = TRUE) 1990 1991 1992 1993 1994 1995 1996 1997
11.99146 11.00885 11.55799 11.45385 12.07944 12.32080 10.72728 12.33687
1998 1999 2000 2001 2002 2003 2004 2005
12.13386 13.10577 12.61539 12.74162 13.05500 12.69017 12.56788 12.56112 tapply(Temp$Salinity, Temp$Year, mean, na.rm = TRUE) 1990 1991 1992 1993 1994 1995 1996 1997
30.89873 30.88625 30.27116 29.52839 29.07707 28.94954 30.66670 30.54525
1998 1999 2000 2001 2002 2003 2004 2005
29.55748 29.03291 28.99534 28.22390 28.89323 29.60946 30.45629 30.35355 tapply(Temp$Temperature, Temp$Year, sd, na.rm = TRUE) 1990 1991 1992 1993 1994 1995 1996 1997
4.710102 5.506477 5.215882 5.009223 5.371933 5.403395 5.754016 6.138538
1998 1999 2000 2001 2002 2003 2004 2005
4.871092 5.608510 4.863818 5.316134 5.308672 6.260190 4.941927 5.240606 tapply(Temp$Salinity, Temp$Year, sd, na.rm = TRUE) 1990 1991 1992 1993 1994 1995 1996 1997
4.576051 4.492322 4.886194 5.964517 6.036686 5.421831 4.300637 4.274470
1998 1999 2000 2001 2002 2003 2004 2005
5.651709 5.747751 5.900264 6.463993 6.019743 5.671687 4.962314 4.451780 Use aggregate() to find average monly temperatures at all stations across all years
aggregate(Temp[,15], list(Temp$Station), mean, na.rm = TRUE) Group.1 x
1 DANT 12.05908
2 DREI 12.77160
3 G6 10.66570
4 GROO 12.25853
5 HAMM 12.50000
6 HANS 13.54894
7 HUIB 11.85353
8 LODS 12.61192
9 MARS 12.39607
10 N02 11.37433
11 N10 12.45878
12 N20 12.19753
13 N70 12.14789
14 R03 12.80000
15 R50 13.94911
16 R70 13.98022
17 SOEL 13.21203
18 T004 11.28425
19 T010 12.37517
20 T100 11.94766
21 T135 11.75512
22 T175 11.55431
23 T235 11.32355
24 VLIS 12.79292
25 W02 10.51829
26 W20 11.87937
27 W70 12.18243
28 WISS 12.45090
29 ZIJP 12.55904
30 ZUID 11.83928aggregate(Temp[,14], list(Temp$Station), mean, na.rm = TRUE) Group.1 x
1 DANT 28.94468
2 DREI 29.83813
3 G6 30.59610
4 GROO 14.57571
5 HAMM 31.35738
6 HANS 18.29124
7 HUIB 29.52631
8 LODS 30.73000
9 MARS 28.03457
10 N02 28.78695
11 N10 30.45223
12 N20 31.93275
13 N70 34.94147
14 R03 30.54978
15 R50 33.49888
16 R70 33.67944
17 SOEL 18.09477
18 T004 32.08114
19 T010 32.72095
20 T100 34.56746
21 T135 34.67667
22 T175 34.75135
23 T235 34.87812
24 VLIS 29.55476
25 W02 32.05992
26 W20 33.31554
27 W70 35.02006
28 WISS 31.75164
29 ZIJP 29.39230
30 ZUID 28.83997Find the number of observations at each station, for each year, and for both using the table() function
table(Temp$Station)
DANT DREI G6 GROO HAMM HANS HUIB LODS MARS N02 N10 N20 N70 R03 R50 R70
300 293 278 296 295 309 296 294 296 402 665 266 268 161 106 106
SOEL T004 T010 T100 T135 T175 T235 VLIS W02 W20 W70 WISS ZIJP ZUID
295 339 261 258 259 258 258 421 272 191 190 296 296 303 table(Temp$Year)
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
367 392 438 436 590 590 583 636 608 570 563 568 545 550 540 552 table(Temp$Year, Temp$Station)
DANT DREI G6 GROO HAMM HANS HUIB LODS MARS N02 N10 N20 N70 R03 R50 R70
1990 12 13 12 12 13 13 12 13 12 12 47 12 12 0 0 0
1991 12 13 16 12 13 16 11 13 12 17 45 12 11 5 5 5
1992 18 13 20 18 13 13 18 13 18 20 40 11 11 7 7 7
1993 19 13 17 19 13 13 19 13 18 17 46 11 11 7 7 7
1994 17 19 21 17 20 21 17 20 16 27 53 18 18 13 10 10
1995 13 21 24 12 21 24 12 21 12 29 56 18 18 17 7 7
1996 19 20 23 18 20 19 19 20 19 31 43 18 18 17 7 7
1997 20 20 28 19 21 19 19 21 19 40 52 18 18 23 7 7
1998 22 21 23 21 20 18 21 20 22 37 45 18 18 20 7 7
1999 21 20 21 21 20 18 21 20 21 29 43 18 19 9 7 7
2000 22 20 13 21 21 29 21 20 21 24 36 19 18 8 7 7
2001 21 20 12 21 20 29 22 20 21 27 37 19 20 7 7 7
2002 21 20 12 21 20 20 21 20 21 23 30 19 20 7 7 7
2003 21 20 12 21 20 19 21 20 21 23 31 19 19 7 7 7
2004 21 20 12 21 20 19 21 20 21 22 29 17 18 7 7 7
2005 21 20 12 22 20 19 21 20 22 24 32 19 19 7 7 7
SOEL T004 T010 T100 T135 T175 T235 VLIS W02 W20 W70 WISS ZIJP ZUID
1990 13 12 12 12 12 12 12 14 12 12 12 13 13 11
1991 13 14 10 10 10 10 10 18 17 12 12 13 13 12
1992 13 20 11 10 10 10 10 21 20 11 11 13 13 18
1993 12 16 10 10 10 10 10 24 17 11 11 13 13 19
1994 20 26 18 18 18 18 18 35 21 12 12 20 20 17
1995 22 27 18 18 18 18 18 36 23 12 12 21 21 14
1996 20 27 18 18 18 18 18 22 23 12 12 20 20 19
1997 21 33 18 18 18 18 18 23 28 12 12 22 23 21
1998 20 28 18 18 18 18 18 22 23 12 12 20 20 21
1999 20 20 18 18 18 18 18 22 16 13 12 20 20 22
2000 20 19 18 18 17 18 18 30 12 12 12 21 20 21
2001 20 19 18 18 19 18 18 31 12 12 12 20 20 21
2002 20 19 18 18 18 18 18 30 12 12 12 20 20 21
2003 20 20 19 18 19 18 18 32 12 12 12 20 20 22
2004 20 19 18 18 18 18 18 31 12 12 12 20 20 22
2005 21 20 19 18 18 18 18 30 12 12 12 20 20 22Now you are done!