[R] Difficulty subsetting data frames using logical operators

Ulrik Stervbo ulrik.stervbo at gmail.com
Sat Jul 2 11:16:34 CEST 2016


Hi Giles,

Look at ?mean

In addition it seems you need to read a few tutorials on R. Several are
already mentioned on this list otherwise Google can direct.

Hope this helps,
Ulrik

Giles Bischoff <gab4 at st-andrews.ac.uk> schrieb am Fr., 1. Juli 2016 18:55:

> So, I uploaded a data set via my directory using the command data <-
> data.frame(read.csv("hw1_data.csv")) and then tried to subset that data
> using logical operators. Specifically, I was trying to make it so that I
> got all the rows in which the values for "Ozone" (a column in the data set)
> were greater than 31 (I was trying to get the mean of all said values).
> Then, I tried using the command data[ , "Ozone">31]. Additionally, I had
> trouble getting it so that I had all the rows where all the values in
> "Ozone">31 & "Temp">90 simultaneously. There were some NA values in both of
> those columns, so that might be it. If someone could help me to figure out
> how to remove those values, that'd be great as well. I'm using a Mac (OS X)
> with the latest version of R (3.1.2. I think??).
>
> Here is some of the code I used:
>
> >data <- data.frame(read.csv("hw1_data.csv"))
> > data
>     Ozone Solar.R Wind Temp Month Day
> 1      41     190  7.4   67     5   1
> 2      36     118  8.0   72     5   2
> 3      12     149 12.6   74     5   3
> 4      18     313 11.5   62     5   4
> 5      NA      NA 14.3   56     5   5
> 6      28      NA 14.9   66     5   6
> 7      23     299  8.6   65     5   7
> 8      19      99 13.8   59     5   8
> 9       8      19 20.1   61     5   9
> 10     NA     194  8.6   69     5  10
> 11      7      NA  6.9   74     5  11
> 12     16     256  9.7   69     5  12
> 13     11     290  9.2   66     5  13
> 14     14     274 10.9   68     5  14
> 15     18      65 13.2   58     5  15
> 16     14     334 11.5   64     5  16
> 17     34     307 12.0   66     5  17
> 18      6      78 18.4   57     5  18
> 19     30     322 11.5   68     5  19
> 20     11      44  9.7   62     5  20
> 21      1       8  9.7   59     5  21
> 22     11     320 16.6   73     5  22
> 23      4      25  9.7   61     5  23
> 24     32      92 12.0   61     5  24
> 25     NA      66 16.6   57     5  25
> 26     NA     266 14.9   58     5  26
> 27     NA      NA  8.0   57     5  27
> 28     23      13 12.0   67     5  28
> 29     45     252 14.9   81     5  29
> 30    115     223  5.7   79     5  30
> 31     37     279  7.4   76     5  31
> 32     NA     286  8.6   78     6   1
> 33     NA     287  9.7   74     6   2
> 34     NA     242 16.1   67     6   3
> 35     NA     186  9.2   84     6   4
> 36     NA     220  8.6   85     6   5
> 37     NA     264 14.3   79     6   6
> 38     29     127  9.7   82     6   7
> 39     NA     273  6.9   87     6   8
> 40     71     291 13.8   90     6   9
> 41     39     323 11.5   87     6  10
> 42     NA     259 10.9   93     6  11
> 43     NA     250  9.2   92     6  12
> 44     23     148  8.0   82     6  13
> 45     NA     332 13.8   80     6  14
> 46     NA     322 11.5   79     6  15
> 47     21     191 14.9   77     6  16
> 48     37     284 20.7   72     6  17
> 49     20      37  9.2   65     6  18
> 50     12     120 11.5   73     6  19
> 51     13     137 10.3   76     6  20
> 52     NA     150  6.3   77     6  21
> 53     NA      59  1.7   76     6  22
> 54     NA      91  4.6   76     6  23
> 55     NA     250  6.3   76     6  24
> 56     NA     135  8.0   75     6  25
> 57     NA     127  8.0   78     6  26
> 58     NA      47 10.3   73     6  27
> 59     NA      98 11.5   80     6  28
> 60     NA      31 14.9   77     6  29
> 61     NA     138  8.0   83     6  30
> 62    135     269  4.1   84     7   1
> 63     49     248  9.2   85     7   2
> 64     32     236  9.2   81     7   3
> 65     NA     101 10.9   84     7   4
> 66     64     175  4.6   83     7   5
> 67     40     314 10.9   83     7   6
> 68     77     276  5.1   88     7   7
> 69     97     267  6.3   92     7   8
> 70     97     272  5.7   92     7   9
> 71     85     175  7.4   89     7  10
> 72     NA     139  8.6   82     7  11
> 73     10     264 14.3   73     7  12
> 74     27     175 14.9   81     7  13
> 75     NA     291 14.9   91     7  14
> 76      7      48 14.3   80     7  15
> 77     48     260  6.9   81     7  16
> 78     35     274 10.3   82     7  17
> 79     61     285  6.3   84     7  18
> 80     79     187  5.1   87     7  19
> 81     63     220 11.5   85     7  20
> 82     16       7  6.9   74     7  21
> 83     NA     258  9.7   81     7  22
> 84     NA     295 11.5   82     7  23
> 85     80     294  8.6   86     7  24
> 86    108     223  8.0   85     7  25
> 87     20      81  8.6   82     7  26
> 88     52      82 12.0   86     7  27
> 89     82     213  7.4   88     7  28
> 90     50     275  7.4   86     7  29
> 91     64     253  7.4   83     7  30
> 92     59     254  9.2   81     7  31
> 93     39      83  6.9   81     8   1
> 94      9      24 13.8   81     8   2
> 95     16      77  7.4   82     8   3
> 96     78      NA  6.9   86     8   4
> 97     35      NA  7.4   85     8   5
> 98     66      NA  4.6   87     8   6
> 99    122     255  4.0   89     8   7
> 100    89     229 10.3   90     8   8
> 101   110     207  8.0   90     8   9
> 102    NA     222  8.6   92     8  10
> 103    NA     137 11.5   86     8  11
> 104    44     192 11.5   86     8  12
> 105    28     273 11.5   82     8  13
> 106    65     157  9.7   80     8  14
> 107    NA      64 11.5   79     8  15
> 108    22      71 10.3   77     8  16
> 109    59      51  6.3   79     8  17
> 110    23     115  7.4   76     8  18
> 111    31     244 10.9   78     8  19
> 112    44     190 10.3   78     8  20
> 113    21     259 15.5   77     8  21
> 114     9      36 14.3   72     8  22
> 115    NA     255 12.6   75     8  23
> 116    45     212  9.7   79     8  24
> 117   168     238  3.4   81     8  25
> 118    73     215  8.0   86     8  26
> 119    NA     153  5.7   88     8  27
> 120    76     203  9.7   97     8  28
> 121   118     225  2.3   94     8  29
> 122    84     237  6.3   96     8  30
> 123    85     188  6.3   94     8  31
> 124    96     167  6.9   91     9   1
> 125    78     197  5.1   92     9   2
> 126    73     183  2.8   93     9   3
> 127    91     189  4.6   93     9   4
> 128    47      95  7.4   87     9   5
> 129    32      92 15.5   84     9   6
> 130    20     252 10.9   80     9   7
> 131    23     220 10.3   78     9   8
> 132    21     230 10.9   75     9   9
> 133    24     259  9.7   73     9  10
> 134    44     236 14.9   81     9  11
> 135    21     259 15.5   76     9  12
> 136    28     238  6.3   77     9  13
> 137     9      24 10.9   71     9  14
> 138    13     112 11.5   71     9  15
> 139    46     237  6.9   78     9  16
> 140    18     224 13.8   67     9  17
> 141    13      27 10.3   76     9  18
> 142    24     238 10.3   68     9  19
> 143    16     201  8.0   82     9  20
> 144    13     238 12.6   64     9  21
> 145    23      14  9.2   71     9  22
> 146    36     139 10.3   81     9  23
> 147     7      49 10.3   69     9  24
> 148    14      20 16.6   63     9  25
> 149    30     193  6.9   70     9  26
> 150    NA     145 13.2   77     9  27
> 151    14     191 14.3   75     9  28
> 152    18     131  8.0   76     9  29
> 153    20     223 11.5   68     9  30
>
>  >colnames(data) <- c("Ozone", "Solar.R", "Wind", "Temp", "Month", "Day")
>
> > mean(data[, Ozone])
> Error in `[.data.frame`(data, , Ozone) : object 'Ozone' not found
>
> mean(data[, "Ozone">31])
> [1] NA
> Warning message:
> In mean.default(data[, "Ozone" > 31]) :
>   argument is not numeric or logical: returning NA
> >  mean(data[, "Ozone">31 & "Ozone"[!is.na("Ozone")]])
> Error in "Ozone" > 31 & "Ozone"[!is.na("Ozone")] :
>   operations are possible only for numeric, logical or complex types
>
>         [[alternative HTML version deleted]]
>
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