R Split Numeric Vector at Position

R split numeric vector at position

An improvement would be:

splitAt <- function(x, pos) unname(split(x, cumsum(seq_along(x) %in% pos)))

which can now take a vector of positions:

splitAt(a, c(2, 4))
# [[1]]
# [1] 1
# 
# [[2]]
# [1] 2 2
# 
# [[3]]
# [1] 3

And it does behave properly (subjective) if pos <= 0 or pos >= length(x) in the sense that it returns the whole original vector in a single list item. If you'd like it to error out instead, use stopifnot at the top of the function.

How to split a character vector based on a numeric vector for positions

We can try substring:

substring(
    vec,
    c(1, split.points + 1),
    c(split.points, nchar(vec))
)
# [1] "LAYRVCMTNEGHPWVSLVVQKTRLQ"                    "ISQDPSL"                                     
# [3] "NYEYLPTMGLKSFIQASLALLFG"                      "KHSQAIVENRVGGVHTVGDSGAFQLGVQFLRAWHK"         
# [5] "DARIVYIISSQKELHGLVFQDMGFTVYEYSVWDP"           "KKLCMDPDILLNVVEQIPHGCVLVMGNIIDCKLTPSGWAKLMSM"

Split all values in column and store them in a single numeric vector

You already have the answer in your code since all the functions you are using are vectorised.

v <- as.numeric(na.omit(unlist(strsplit(df$col, ','))))
v
#[1]  2  6 10  5 10  1

Split named numeric vector into different elements in R

Here is one base R approach :

#Repeat each value in obj, obj number of times
res <- rep(obj, obj)
#Change all values to 1.
res[] <- 1
#Change the names
names(res) <- ave(names(res), names(res), FUN = function(x) 
                  if(length(x) == 1) x else paste(x, seq_along(x), sep = '_'))
res

# V4_1  V4_2  V4_3   V10   V12   V15 V16_1 V16_2 V16_3 V16_4 V16_5 V16_6 
#    1     1     1     1     1     1     1     1     1     1     1     1 
#  V20   V21   V22   V23   V36   V39   V40   V41 V42_1 V42_2 V42_3 
#    1     1     1     1     1     1     1     1     1     1     1 

Split vector by location

Both the previous answers rely on making lists/vectors for splitting that are the same length as the original x vector. This might be inefficient in the instance of a very long vector and can be avoided:

Map(function(i,j) x[i:j], a, cumsum(diff(c(a, length(x)+1))))

Split a numeric vector into continuous chunks in R

Here's another alternative:

vec <- c( 1, 2, 3, 4, 7, 8, 9, 10, 15, 16, 17 )
split(vec, cumsum(seq_along(vec) %in% (which(diff(vec)>1)+1)))
# $`0`
# [1] 1 2 3 4
# 
# $`1`
# [1]  7  8  9 10
# 
# $`2`
# [1] 15 16 17

Splitting numeric vectors in R

Here's one way using cut and split:

split(x, cut(x, c(-Inf, y, Inf)))
#$`(-Inf,3]`
#[1] 1 2 3
#
#$`(3,7]`
#[1] 5 7
#
#$`(7,10]`
#[1]  9 10
#
#$`(10, Inf]`
#[1] 12

Split string by position and numeric value in dplyr

Here's a verbose approach that might be helpful as you refine for edge cases.

library(tidyverse)

# combine splits @ 2 and @ 3
bind_rows(df1 %>% mutate(split_pos = 2),
          df1 %>% mutate(split_pos = 3)) %>%
  
# calc features
  mutate(num1 = str_sub(to_split,   end = split_pos)     %>% parse_number(),
         num2 = str_sub(to_split, start = split_pos + 1) %>% parse_number(),
         total = num1 + num2,
         max = pmax(num1, num2)) %>%
  
# filter and pick best fit
  filter(total %>% between(100, 250), max <= 150) %>%
  arrange(id) %>%
  group_by(id) %>%
  slice_min(max) %>%
  ungroup()



    id to_split split_pos  num1  num2 total   max
  <dbl> <chr>        <dbl> <dbl> <dbl> <dbl> <dbl>
1     1 33118            2    33   118   151   118
2     2 37118            2    37   118   155   118
3     3 30121            2    30   121   151   121
4     4 41110            2    41   110   151   110
5     5 98121            2    98   121   219   121
6     6 101102           3   101   102   203   102
7     7 101110           3   101   110   211   110
8     8 10148            3   101    48   149   101
9     9 11121            3   111    21   132   111

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