[英]Efficiently adding column to dataframe based on values from regex capture groups from other columns
I wanted to add an additional column to an existing dataframe where the value of newColumn would be based on a capture group of a regex applied to another value in the same row and the only thing I came up with that worked so far was this (probably not R-esque) standard-approach of looping but it is awefully slow (for a DF of around 1.5 million rows).我想向现有数据框添加一个额外的列,其中newColumn的值将基于应用于同一行中另一个值的正则表达式的捕获组,到目前为止我想出的唯一有效的是这个(可能不是 R 式)循环的标准方法,但它非常慢(对于大约 150 万行的 DF)。
Dataframe with Columns:带列的数据框:
ID Text NewColumn
Atm I work with this: Atm 我处理这个:
df$newColumn <- rep("", nrow(df));
for (row in 1:nrow(df)) {
df$newColumn[row] <- str_match(df$Text[row], regex)[1,2];
}
I tried using apply/lapply after reading several posts but none of my approaches created the expected result.在阅读了几篇文章后,我尝试使用 apply/lapply 但我的方法都没有产生预期的结果。 Is this even possible with a function of the apply-family, and if yes: how?这甚至可以通过 apply-family 的功能实现,如果是:如何?
Example:例子:
for为了
regex <- "^[0-9]*([a-zA-Z]*)$";
and a table like the following:和如下表:
ID Text
------------------
1 231Ben
2 112Claudine
3 538Julia
I would expect:我希望:
ID Text NewColumn
----------------------------
1 231Ben Ben
2 112Claudine Claudine
3 538Julia Julia
The str_match
and gsub/sub
etc are vectorized, so we don't have to loop through the rows if the pattern
is the same str_match
和gsub/sub
等是矢量化的,所以如果pattern
相同,我们不必遍历行
df1$NewColumn <- gsub("\\d+", "", df1$Text)
Or with stringr
functions或者使用stringr
函数
library(stringr)
df1$NewColumn <- str_match(df1$Text, "([A-Za-z]+)")[,1]
str_extract(df1$Text, "[A-Za-z]+")
#[1] "Ben" "Claudine" "Julia"
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