Make a table showing the 10 largest values of a variable in R?

Question

I want to make a simple table that showcases the largest 10 values for a given variable in my dataset, as well as 4 other variables for each observation, so basically a small su

Answer 1

This should do it...

data <- data[with(data,order(-Score)),]

data <- data[1:10,]

Answer 2

Using sqldf:

library(sqldf)
sqldf("SELECT * FROM mtcars 
      ORDER BY mpg DESC 
      LIMIT 10", row.names = TRUE)

Output:

               mpg cyl  disp  hp drat    wt  qsec vs am gear carb
Toyota Corolla 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
Fiat 128       32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
Honda Civic    30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
Lotus Europa   30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
Fiat X1-9      27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
Porsche 914-2  26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
Merc 240D      24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
Datsun 710     22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
Merc 230       22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
Toyota Corona  21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1

Answer 3

You can get the highest values of a vector using the code below:

my_vec <- c(1:100)
tail(sort(my_vec),10)

So if you want to use this method as a data frame filter you could do:

data(mtcars)
mtcars[mtcars$mpg %in% tail(sort(mtcars$mpg),4),]

which would produce:

> mtcars[mtcars$mpg %in% tail(sort(mtcars$mpg),4),]
                mpg cyl disp  hp drat    wt  qsec vs am gear carb
Fiat 128       32.4   4 78.7  66 4.08 2.200 19.47  1  1    4    1
Honda Civic    30.4   4 75.7  52 4.93 1.615 18.52  1  1    4    2
Toyota Corolla 33.9   4 71.1  65 4.22 1.835 19.90  1  1    4    1
Lotus Europa   30.4   4 95.1 113 3.77 1.513 16.90  1  1    5    2

Answer 4

You can do this using arrange from dplyr. This should also work if there are grouping variables. Just add group_by before the arrange. We filter the first 10 observations using slice.

 library(dplyr)
 df1 %>%
    arrange(desc(Score)) %>%
    slice(1:10) 

Or another option is ?top_n (commented by @docendodiscimus) from dplyr which is a wrapper that uses filter and min_rank to select the top n (i.e. 10) entries for 'Score'.

 top_n(df1, 10, Score)    

Or we use filter by creating a logical condition with row_number which is equivalent to rank(ties.method='first') (contributed by @Steven Beaupre)

 filter(df1, row_number(desc(Score)) <= 10)

Or a data.table option (by @David Arenburg). We convert the 'data.frame' to 'data.table' (setDT(df1)), order (decreasing) the 'Score' variable, and select the first 10 observations. .SD means Subset of DataTable.

 library(data.table)
 setDT(df1)[order(-Score), .SD[1:10]]