Using dplyr mutate to find position of character in string - regex

Question

I have data frame with a column of strings, that of an number id followed by "-" and then a month year. I am trying to parse the string to get the month and year. As a very first step, I used dplyr::mutate() and
regexpr()
regexpr("-",yearid)[1]
to create a new column that shows the position of this "-" character. But seems like regexpr() performs very differently inside a mutate(), than when used separately. It does not seem to update depending on the string, but carries over the string position from previous rows. In the example below I expect the position of "-" character to be 4,4, and 5 in the respective yearid. But I get 4,4, and 4 - so this 4 is not correct. When I run regexpr separately I dont see this issue.
Wondering if I am missing something, and how can I get position of "-" dynamically that is specific for each value of yearid? May be there is an easier way to get January, and 1997.
yearid <- c("50 - January 1995","51 - January 1996","100 - January 1997")
data.df <- data.frame(yearid)
data.df <- mutate(data.df, trimpos = regexpr("-",str_trim(yearid))[1],
pos = regexpr("-",yearid)[1])
> data.df
yearid test1 test2
1 50 - January 1995 4 4
2 51 - January 1996 4 4
3 100 - January 1997 4 4
On the other hand using regexpr as such I get the output as expected:
> regexpr("-",yearid[1])[1]
[1] 4
> regexpr("-",yearid[2])[1]
[1] 4
> regexpr("-",yearid[3])[1]
[1] 5
Finally, I have my sessionInfo() below
R version 3.1.1 (2014-07-10)
Platform: x86_64-apple-darwin10.8.0 (64-bit)
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] stringr_1.0.0 dplyr_0.4.1 readr_0.2.2.9000
loaded via a namespace (and not attached):
[1] assertthat_0.1 DBI_0.3.1 knitr_1.10.5 lazyeval_0.1.10.9000 magrittr_1.5 parallel_3.1.1
[7] Rcpp_0.11.6 stringi_0.4-1 tools_3.1.1

Answer 1

The regexpr function from the stringr library returns a vector of positions with two additional attributes attached match.length and useBytes. As mentioned in the comments, this vector can be assigned directly to the data frame. This can be done using the mutate function or without.
library(dplyr)
library(stringr)
id_month_year <- c(
"50 - January 1995",
"51 - January 1996",
"100 - January 1997"
)
data <- data.frame(id_month_year, another_column = 1)
## create new column using mutate
data <- data %>% mutate(pos1 = regexpr("-", data$id_month_year))
## create new column without mutate
data$pos2 <- regexpr("-", data$id_month_year)
print(data)
Here are the new columns:
id_month_year another_column pos1 pos2
1 50 - January 1995 1 4 4
2 51 - January 1996 1 4 4
3 100 - January 1997 1 5 5
I would suggest using the separate function from the tidyr library. Here's an example code snippet:
library(dplyr)
library(tidyr)
id_month_year <- c(
"50 - January 1995",
"51 - January 1996",
"100 - January 1997"
)
data <- tbl_df(data.frame(id_month_year, another_column = 1))
clean <- data %>%
separate(
id_month_year,
into = c("id", "month", "year"),
sep = "[- ]+",
convert = TRUE
)
print(clean)
And here's the resulting clean data frame:
Source: local data frame [3 x 4]
id month year another_column
(int) (chr) (int) (dbl)
1 50 January 1995 1
2 51 January 1996 1
3 100 January 1997 1