Generating Sequence from values of 2 columns in a dataframe

[smpa01]

Hi,

I have a dataframe as following

Start <- c(1, 6,11,15)
End <- c(5,10,11,17)
df <- data.frame(Start,End)

Sample_Data_File

Is it possible to generate a dataframe with a 3rd column that will keep the integers in sequence between Start and End values.

I attached an excel file with input and desired output in dataframe.

Any help is greatly appreciated. I am extremely new to R.

Thank you in advance.

[Yarnabrina]

Welcome to R!

Are you looking for something like this?

Start <- c(1, 6, 11, 15)
End <- c(5, 10, 11, 17)
df <- data.frame(Start,
                 End)
Custom <- c()
for (i in seq_along(along.with = Start))
{
  Custom <- c(Custom, Start[i]:End[i])
}
lengths <- (End - Start + 1)
df <- cbind(Start = rep.int(x = Start,
                            times = lengths),
            End = rep.int(x = End,
                          times = lengths),
            Custom)

^{Created on 2019-03-12 by the reprex package (v0.2.1)}

Hope this helps.

[smpa01]

@Yarnabrina thanks for your response.It perfectly works in R and I have my desired output.

However, I was intending to get this output by running the same code in the R console in Power BI. The code fails in Power BI.

Anyway, thanks for the help.

[joels]

Here's an approach using a dplyr pipe and nesting:

library(tidyverse)

df %>% 
  # Need to operate by row, so group by row number
  group_by(r=row_number()) %>% 
  # Create nested list column containing the sequence for each pair of Start, End values
  mutate(custom = list(Start:End)) %>% 
  # Remove the row-number column, which is no longer needed
  ungroup %>% select(-r) %>% 
  # Unnest the list column to get the desired "long" data frame
  unnest()

   Start   End custom
   <dbl> <dbl>  <int>
 1     1     5      1
 2     1     5      2
 3     1     5      3
 4     1     5      4
 5     1     5      5
 6     6    10      6
 7     6    10      7
 8     6    10      8
 9     6    10      9
10     6    10     10
11    11    11     11
12    15    17     15
13    15    17     16
14    15    17     17

Another option is to create a vectorized helper function that inherently operates by row:

fnc = Vectorize(function(x,y) x:y)

df %>% 
  mutate(custom = fnc(Start, End)) %>% 
  unnest()