get 95 percentile outliers in column in r

To get the 95 percentile outliers in a column in R, you can follow these steps:

1. Load your data into R. For example, if your data is stored in a CSV file named "mydata.csv", you can use the read.csv() function to load it into R:

main.r
mydata <- read.csv("mydata.csv")
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2. Calculate the 95th percentile of the column using the quantile() function:

main.r
percentile <- quantile(mydata$mycolumn, 0.95)
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Replace "mycolumn" with the name of the column containing the data you want to analyze.

3. Identify the outliers in the column by comparing each value to the 95th percentile:

main.r
outliers <- subset(mydata, mycolumn > percentile)
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This will create a new data frame called "outliers" that contains all the rows where the value in the "mycolumn" column is greater than the 95th percentile.

That's it! You now have a data frame with all the outliers in the column you were analyzing. You can further analyze or visualize this data to gain insights into your data set.