R – Sorting A Data Frame By The Contents Of A Column - R-bloggers

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Let’s examine how to sort the contents of a data frame by the value of a column

> numPeople = 10 > sex=sample(c("male","female"),numPeople,replace=T) > age = sample(14:102, numPeople, replace=T) > income = sample(20:150, numPeople, replace=T) > minor = age<18

This last statement might look surprising if you’re used to Java or a traditional programming language. Rather than becoming a single boolean/truth value, minor actually becomes a vector of truth values, one per row in the age column.  It’s equivalent to the much more verbose code in Java:

int[] age= ...; for (int i = 0; i < income.length; i++) {    minor[i] = age[i] < 18; }

Just as expected, the value of minor is a vector:

> mode(minor) [1] "logical" > minor [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE

Next we create a data frame, which groups together our various vectors into the columns of a data structure:

> population = data.frame(sex=sex, age=age, income=income, minor=minor) > population sex age income minor 1    male  68    150 FALSE 2    male  48     21 FALSE 3  female  68     58 FALSE 4  female  27    124 FALSE 5  female  84    103 FALSE 6    male  92    112 FALSE 7    male  35     65 FALSE 8  female  15    117  TRUE 9    male  89     95 FALSE 10   male  26     54 FALSE

The arguments (sex=sex, age=age, income=income, minor=minor) assign the same names to the columns as I originally named the vectors; I could just as easily call them anything.  For instance,

> data.frame(a=sex, b=age, c=income, minor=minor) a  b   c minor 1    male 68 150 FALSE 2    male 48  21 FALSE 3  female 68  58 FALSE 4  female 27 124 FALSE 5  female 84 103 FALSE 6    male 92 112 FALSE 7    male 35  65 FALSE 8  female 15 117  TRUE 9    male 89  95 FALSE 10   male 26  54 FALSE

But I prefer the more descriptive labels I gave previously.

> population sex age income minor 1    male  68    150 FALSE 2    male  48     21 FALSE 3  female  68     58 FALSE 4  female  27    124 FALSE 5  female  84    103 FALSE 6    male  92    112 FALSE 7    male  35     65 FALSE 8  female  15    117  TRUE 9    male  89     95 FALSE 10   male  26     54 FALSE

Now let's say we want to order by the age of the people. To do that is a one liner:

> population[order(population$age),] sex age income minor 8  female  15    117  TRUE 10   male  26     54 FALSE 4  female  27    124 FALSE 7    male  35     65 FALSE 2    male  48     21 FALSE 1    male  68    150 FALSE 3  female  68     58 FALSE 5  female  84    103 FALSE 9    male  89     95 FALSE 6    male  92    112 FALSE

This is not magic; you can select arbitrary rows from any data frame  with the same syntax:

> population[c language="(1,2,3),"][/c] sex age income minor 1   male  68    150 FALSE 2   male  48     21 FALSE 3 female  68     58 FALSE

The order function merely returns the indices of the rows in sorted order.

> order(population$age) [1]  8 10  4  7  2  1  3  5  9  6

Note the $ syntax; you select columns of a data frame by using a dollar sign and the name of the column. You can retrieve the names of the columns of a data frame with the names function.

> names(population) [1] "sex"    "age"    "income" "minor" > population$income [1] 150  21  58 124 103 112  65 117  95  54 > income [1] 150  21  58 124 103 112  65 117  95  54

As you can see, they are exactly the same.

So what we're really doing with the command

population[order(population$age),]

is

population[c language="(8,10,4,7,2,1,3,5,9,6),"][/c]

Note the trailing comma; what this means is to take all the columns. If we only wanted certain columns, we could specify after this comma.

> population[order(population$age),c(1,2)] sex age 8  female  15 10   male  26 4  female  27 7    male  35 2    male  48 1    male  68 3  female  68 5  female  84 9    male  89 6    male  92

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