计算 r 中单词向量中特定字母的出现次数 [英] counting occurrence of particular letter in vector of words in r

问题描述

我正在尝试计算长单词向量中特定字母的数量.

I am trying to count number of particular letter in long vector of words.

例如:

我想计算以下向量中字母A"的数量.

I would like to count number of letter "A" in the following vector.

myvec <- c("A", "KILLS", "PASS", "JUMP", "BANANA", "AALU", "KPAL")

所以预期的输出是:

c(1,0,1,0, 3,2,1)

有什么想法吗?

推荐答案

另一种可能性:

myvec <- c("A", "KILLS", "PASS", "JUMP", "BANANA", "AALU", "KPAL")

sapply(gregexpr("A", myvec, fixed = TRUE), function(x) sum(x > -1))

## [1] 1 0 1 0 3 2 1

编辑这是在乞求一个基准:

library(stringr); library(stringi); library(microbenchmark); library(qdapDictionaries)

myvec <- toupper(GradyAugmented)

GREGEXPR <- function() sapply(gregexpr("A", myvec, fixed = TRUE), function(x) sum(x > -1))
GSUB <- function() nchar(gsub("[^A]", "", myvec))
STRSPLIT <- function() sapply(strsplit(myvec,""), function(x) sum(x=='A'))
STRINGR <- function() str_count(myvec, "A")
STRINGI <- function()  stri_count(myvec, fixed="A")
VAPPLY_STRSPLIT <- function() vapply(strsplit(myvec,""), function(x) sum(x=='A'), integer(1))


(op <- microbenchmark( 
    GREGEXPR(),
    GSUB(),
    STRINGI(),
    STRINGR(),
    STRSPLIT(),
    VAPPLY_STRSPLIT(),    
times=50L))

## Unit: milliseconds
##               expr        min         lq       mean     median        uq        max neval
##         GREGEXPR() 477.278895 631.009023 688.845407 705.878827 745.73596  906.83006    50
##             GSUB() 197.127403 202.313022 209.485179 205.538073 208.90271  270.19368    50
##          STRINGI()   7.854174   8.354631   8.944488   8.663362   9.32927   11.19397    50
##          STRINGR() 618.161777 679.103777 797.905086 787.554886 906.48192 1115.59032    50
##         STRSPLIT() 244.721701 273.979330 331.281478 294.944321 348.07895  516.47833    50
##  VAPPLY_STRSPLIT() 184.042451 206.049820 253.430502 219.107882 251.80117  595.02417    50

boxplot(op)

和stringi 大尾巴.vapply + strsplit 是一个很好的方法，就像简单的 gsub 方法一样.肯定会有有趣的结果.

And stringi whooping some major tail. The vapply + strsplit was a nice approach as was the simple gsub approach. Interesting results for sure.

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