How to find top n% of records in a column of a dataframe using R

I have a dataset showing the exchange rate of the Australian Dollar versus the US dollar once a day over a period of about 20 years. I have the data in a data frame, with the first column being the date, and the second column being the exchange rate. Here's a sample from the data:

>data
             V1     V2
1    12/12/1983 0.9175
2    13/12/1983 0.9010
3    14/12/1983 0.9000
4    15/12/1983 0.8978
5    16/12/1983 0.8928
6    19/12/1983 0.8770
7    20/12/1983 0.8795
8    21/12/1983 0.8905
9    22/12/1983 0.9005
10   23/12/1983 0.9005

How would I go about displaying the top n% of the开发者_如何学编程se records? E.g. say I want to see the days and exchange rates for those days where the exchange rate falls in the top 5% of all exchange rates in the dataset?

For the top 5%:

n <- 5
data[data$V2 > quantile(data$V2,prob=1-n/100),]

For the top 5% also:

head(data[order(data$V2,decreasing=T),],.05*nrow(data))

Another solution could be use for sqldf if the data is sorted based on the V1 value:

library(sqldf)
sqldf('SELECT * FROM df
       ORDER BY V1
       LIMIT (SELECT 0.05 * COUNT(*) FROM df)
      ') 

You can change the rate form 0.05 (5%) to any required rate.

A dplyr solution could look like this:

obs <- nrow(data) 
data %>% filter(row_number() < obs * 0.05)

This only works if the data is sorted, but your question and example data implies this. If the data is unsorted, you will need to arrange it by the variable you're interested in:

data <- data %>% arrange(desc(V2))