R: subset dataframe by column value found in a separate vector, keeping duplicates

Question

Suppose I have a vector containing a sequence of radii in a, and the area and circumference for radii from 1 through 30 in circle_stats. I want to subset circle_stats such that the rows match those found in a.

a <- as.character(c(1,2,3,4,5,5,6,7,2,8,4,9,10,10,1,1,1,1,1,4))
unique(a[duplicated(a)])
# these are the duplicated values
# 5 2 4 10 1

radius <- c(1:30)
circle_stats <- data.frame(radius=as.character(radius),
                           area=pi*radius^2,
                           circumference=2*pi*radius)

This would also mean being able to keep duplicates instead of discarding them, or 20 rows subsetted from circle_stats instead of just 10.

This is what I tried:

library(data.table)
circle_stats %>% 
  subset(radius %in% a) %>%
  arrange(match(radius, a))

   radius       area circumference
1       1   3.141593      6.283185
2       2  12.566371     12.566371
3       3  28.274334     18.849556
4       4  50.265482     25.132741
5       5  78.539816     31.415927
6       6 113.097336     37.699112
7       7 153.938040     43.982297
8       8 201.061930     50.265482
9       9 254.469005     56.548668
10     10 314.159265     62.831853

As you can see, the issue is that I can't keep duplicates, which I assume requires an argument or function within the subset function. I just can't figure out which one.

Any help is greatly appreciated!

edit: originally the question considered numerical values, but the dataset I'm working with uses character values in a and circle_stats$radius.

Answer 1

Thank you @lotus for the answer:

library(dplyr)
circle_stats %>% 
    dplyr::slice(match(a, radius))


   radius       area circumference
1       1   3.141593      6.283185
2       2  12.566371     12.566371
3       3  28.274334     18.849556
4       4  50.265482     25.132741
5       5  78.539816     31.415927
6       5  78.539816     31.415927
7       6 113.097336     37.699112
8       7 153.938040     43.982297
9       2  12.566371     12.566371
10      8 201.061930     50.265482
11      4  50.265482     25.132741
12      9 254.469005     56.548668
13     10 314.159265     62.831853
14     10 314.159265     62.831853
15      1   3.141593      6.283185
16      1   3.141593      6.283185
17      1   3.141593      6.283185
18      1   3.141593      6.283185
19      1   3.141593      6.283185
20      4  50.265482     25.132741