[英]Calculate percentile for every column in a data frame in R
I have a data set of 3 categorial columns and 40 columns with numerical values. 我有一个包含3个分类列和40个数值的数据集。 I want to calculate the 90th percentile for each of the 40 numerical columns separetly.
我想计算出40个数字列中每个列的第90个百分位数。
Take this data frame as a reproducible example: 将此数据框作为可重现的示例:
fruit = c("apple","orange","banana","berry") #1st col
ID = c(123,3453,4563,3235) #2nd col
price1 = c(3,5,10,20) #3rd col
price2 = c(5,7,9,2) #4th col
price3 = c(4,1,11,8) #5th col
df = data.frame(fruit,ID,price1,price2,price3) #combine into a dataframe
I want to do something like: calc_percentile = quantile(df[,3:5], probs = 0.90)
我想做类似的事情:
calc_percentile = quantile(df[,3:5], probs = 0.90)
The output I'm looking for would be: 我正在寻找的输出将是:
# Column 90thPercentile
# price1 17
# price2 8.4
# price3 10.1
Doing this one by one is not practical given that I have 40 columns. 鉴于我有40列,这样做是不切实际的。 Your help is appreciated!
非常感谢您的帮助!
stack(lapply(df[3:5], quantile, prob = 0.9, names = FALSE))
# values ind
#1 17.0 price1
#2 8.4 price2
#3 10.1 price3
Using dplyr
and tidyr
: 使用
dplyr
和tidyr
:
df %>%
summarise_at(3:5, ~ quantile(., probs = 0.9)) %>%
gather("Column", "90thPercentile")
Column 90thPercentile
1 price1 17.0
2 price2 8.4
3 price3 10.1
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