Command For Creating Subset Data In R Studio Mac

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Version info: Code for this page was tested in R version 3.0.2 (2013-09-25) On: 2013-11-19 With: lattice 0.20-24; foreign 0.8-57; knitr 1.5 1. Subsetting variables To manipulate data frames in R we can use the bracket notation to access the indices for the observations and the variables. It is easiest to think of the data frame as a rectangle of data where the rows are the observations and the columns are the variables. Just like in matrix algebra, the indices for a rectangle of data follow the RxC principle; in other words, the first index is for Rows and the second index is for Columns [R, C]. When we only want to subset variables (or columns) we use the second index and leave the first index blank.

Leaving an index blank indicates that you want to keep all the elements in that dimension. In the first example we create the data frame hsb3 containing only the variables id, read and write, but all the observations from the original data frame hsb2.small.

Well, R has several ways of doing this in a process it calls “subsetting.” The most basic way of subsetting a data frame in R is by using square brackets such that in: example[x,y] example is the data frame we want to subset, ‘x’ consists of the rows we want returned, and ‘y’ consists of the columns we want returned.

In order to know which variables correspond to which number in the index we use the names function, which will list the names of the variables in the order in which they appear in the data frame. From this list we see that id is variable 1, read is variable 7 and write is variable 8. We cannot refer to the variables by their names alone until we have attached the data. ## id read write ## 1 70 57 52 ## 2 121 68 59 ## 3 86 44 33 ## 4 141 63 44 ## 5 172 47 52 ## 6 113 44 52 ## 7 50 50 59 ## 8 11 34 46 ## 9 84 63 57 ## 10 48 57 55 ## 11 75 60 46 ## 12 60 57 65 ## 13 95 73 60 ## 14 104 54 63 ## 15 38 45 57 ## 16 115 42 49 ## 17 76 47 52 ## 18 195 57 57 ## 19 114 68 65 ## 20 85 55 39 ## 21 167 63 49 ## 22 143 63 63 ## 23 41 50 40 ## 24 20 60 52 ## 25 12 37 44 If the variables we want are in consecutive columns, we can use the colon notation rather than list them using the c function. In the next example we create the data frame hsb4 containing the first four variables of hsb2.small.

Android emulator react native on mac computer. ## id female race ses ## 1 70 0 4 1 ## 2 121 1 4 2 ## 3 86 0 4 3 ## 4 141 0 4 3 ## 5 172 0 4 2 ## 6 113 0 4 2 ## 7 50 0 3 2 ## 8 11 0 1 2 ## 9 84 0 4 2 ## 10 48 0 3 2 ## 11 75 0 4 2 ## 12 60 0 4 2 ## 13 95 0 4 3 ## 14 104 0 4 3 ## 15 38 0 3 1 ## 16 115 0 4 1 ## 17 76 0 4 3 ## 18 195 0 4 2 ## 19 114 0 4 3 ## 20 85 0 4 2 ## 21 167 0 4 2 ## 22 143 0 4 2 ## 23 41 0 3 2 ## 24 20 0 1 3 ## 25 12 0 1 2 2. Subsetting observations We subset observations by also using the bracket notation but now we use the first index and leave the second index blank. This indicates that we want all the variables for specific observations.

In the first example we create the data frame hsb5, which contains the first 10 observations of hsb2.small. ## id female race ses schtyp prog read write math science socst ## 1 70 0 4 1 1 1 57 52 41 47 57 ## 2 121 1 4 2 1 3 68 59 53 63 61 ## 3 86 0 4 3 1 1 44 33 54 58 31 ## 4 141 0 4 3 1 3 63 44 47 53 56 ## 5 172 0 4 2 1 2 47 52 57 53 61 ## 6 113 0 4 2 1 2 44 52 51 63 61 ## 7 50 0 3 2 1 1 50 59 42 53 61 ## 8 11 0 1 2 1 2 34 46 45 39 36 ## 9 84 0 4 2 1 1 63 57 54 58 51 ## 10 48 0 3 2 1 2 57 55 52 50 51 We can also subset observations based on logical tests. In the following example we create the data frame hsb6, which contains only the observations for which ses=1. For a logical equality we need to use the double equal sign notation. We also need to refer to the variable, ses in the data frame hsb2.small, which we do using $.

## id female race ses schtyp prog read write math science socst ## 1 70 0 4 1 1 1 57 52 41 47 57 ## 15 38 0 3 1 1 2 45 57 50 31 56 ## 16 115 0 4 1 1 1 42 49 43 50 56 In the previous example we used a logical test to subset the observations, but we only tested for one variable being equal to a single value. We can also subset using a logical test that will test a single variable being equal to the elements in a list, and we do this by using the%in% function. In the following example we create the data frame hsb7, which contains the observations where id is equal to 11, 12, 20, 48, 86 or 195. ## id female race ses schtyp prog read write math science socst ## 3 86 0 4 3 1 1 44 33 54 58 31 ## 8 11 0 1 2 1 2 34 46 45 39 36 ## 10 48 0 3 2 1 2 57 55 52 50 51 ## 18 195 0 4 2 2 1 57 57 60 58 56 ## 24 20 0 1 3 1 2 60 52 57 61 61 ## 25 12 0 1 2 1 3 37 44 45 39 46 It is also possible to combine logical tests. In the following example we create the data frame hsb8, which contains only the observations where ses=3 and female=0. Here to avoid having to type hsb2.small multiple times, we use the with function to let R know that it should look for ses and female inside the hsb2.small data frame.