Module 11 Exercise

Author

u1535008

Module 11 Exercise

Read in the data using fread.

library(data.table)
temp <- fread("Temperature.csv")

Extract all winter observations.

winter <- temp[Season == "winter"]
head(winter)

          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.

AST <- temp[, .(Area, Season, Temperature)]
head(AST)

     Area Season Temperature
   <char> <char>       <num>
1:     WZ winter         4.0
2:     WZ winter         6.0
3:     WZ spring         7.3
4:     WZ spring         8.2
5:     WZ spring        17.4
6:     WZ summer        18.1

Select only the columns Area and Temperature, but only for winter observations

ATwinter <- temp[Season == "winter", .(Area, Temperature)]
head(ATwinter)

     Area Temperature
   <char>       <num>
1:     WZ         4.0
2:     WZ         6.0
3:     WZ         4.2
4:     WZ        -0.3
5:     WZ         3.9
6:     WZ         3.9

Find the total number of observations in winter

wintertot <- temp[Season == "winter", .N]
wintertot

[1] 1706

Calculate the mean temperature and mean salinity in winter

winterTS <- temp[Season == "winter", 
                 .(mTemp = mean(Temperature, na.rm = TRUE), 
                   mSal = mean(Salinity, na.rm = TRUE))]
winterTS

     mTemp     mSal
     <num>    <num>
1: 5.57162 29.15756

Find the number of observations per station in winter

winterstat <- temp[Season == "winter", .N, by = .(Station)]
winterstat

    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

obStatSeas <- temp[, .N, by = .(Station, Season)]
obStatSeas

     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

monavgtemp <- temp[, .(mavg = mean(Temperature, na.rm = TRUE)), by = .(Month)]
monavgtemp

    Month      mavg
    <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

avgtempmonarea <- temp[, .(avg = mean(Temperature, na.rm = TRUE)), by = .(Month, Area)]
avgtempmonarea

     Month   Area       avg
     <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

library(ggplot2)
ggplot(avgtempmonarea, aes(x = Month, y = avg, col = Area)) + geom_line()