[R] Difficulty subsetting data frames using logical operators
jim holtman
jholtman at gmail.com
Fri Jul 1 20:47:16 CEST 2016
You may need to re-read the Intro to R.
data[data$Ozone > 31,]
or
subset(data, Ozone > 31)
Jim Holtman
Data Munger Guru
What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to do it.
On Fri, Jul 1, 2016 at 5:11 AM, Giles Bischoff <gab4 at st-andrews.ac.uk>
wrote:
> 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
>
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>
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