In R: How can I check that I have consecutive years of data (to later be able to calculate growth)? - r

Question

I have the dataframe (sample) below:
companyID year yearID
1 2010 1
1 2011 2
1 2012 3
1 2013 4
2 2010 1
2 2011 2
2 2016 3
2 2017 4
2 2018 5
3 2010 1
3 2011 2
3 2014 3
3 2017 4
3 2018 5
I have used a for loop in order to try and create a sequence column that starts a new number for each new sequence of numbers. I am new to R so my definitions may be a bit wrong. My for loop looks like this:
size1 <- c(1:3)
s <- 0
for (val1 in size) {
m <- max(sample[sample$companyID == val1, 4])
size2 <- c(1:m)
for (val2 in size2){
row <- sample[which(sample$companyID == val1 & sample$yearID == val2)]
m1 <- sample[sample$companyID == val1 & sample$yearID == val2, 2]
m2 <- sample[sample$CompanyID == val1 & sample$yearID == (val2-1), 2]
if(val2>1 && m1-m2 > 1) {
sample$sequence[row] s = s+1}
else {s = s}
}
}
Where m is the max value of the yearID per companyID, row is to identify that the value should be entered on the row where companyID = val1 and yearID = val2, m1 is from the year variable and is the latter year, whereas m2 is the former year. What I have tried to do is to change the sequence every time m1-m2 > 1 (when val2 > 1 also).
Desired outcome:
companyID year yearID sequence
1 2010 1 1
1 2011 2 1
1 2012 3 1
1 2013 4 1
2 2010 1 2
2 2011 2 2
2 2016 3 3
2 2017 4 3
2 2018 5 3
3 2010 1 4
3 2011 2 4
3 2014 3 5
3 2017 4 6
3 2018 5 6
Super appreciative if anyone can help!!

Answer 1

This is a good question!
First group_by companyID
calculate the difference of each consecutive row in year column with lag to identify if year is consecutive.
group_by companyID, yearID)
mutate helper column sequence1 to apply 1 to each starting consecutive year in group.
ungroup and apply a sequence number eachtime 1
occurs in sequence1
remove column sequence1 and deltalag1
library(tidyverse)
df1 <- df %>%
group_by(companyID) %>%
mutate(deltaLag1 = year - lag(year, 1)) %>%
group_by(companyID, yearID) %>%
mutate(sequence1 = case_when(is.na(deltaLag1) | deltaLag1 > 1 ~ 1,
TRUE ~ 2)) %>%
ungroup() %>%
mutate(sequence = cumsum(sequence1==1)) %>%
select(-deltaLag1, -sequence1)
data
df <- tribble(
~companyID, ~year, ~yearID,
1, 2010, 1,
1, 2011, 2,
1, 2012, 3,
1, 2013, 4,
2, 2010, 1,
2, 2011, 2,
2, 2016, 3,
2, 2017, 4,
2, 2018, 5,
3, 2010, 1,
3, 2011, 2,
3, 2014, 3,
3, 2017, 4,
3, 2018, 5)

Answer 2

It's not clear if you want the exact desired outcome or check that you have consecutive years by companyID.
According to your title message:
sample <- read.table(header = TRUE, text = "
companyID year yearID
1 2010 1
1 2011 2
1 2012 3
1 2013 4
2 2010 1
2 2011 2
2 2016 3
2 2017 4
2 2018 5
3 2010 1
3 2011 2
3 2014 3
3 2017 4
3 2018 5
")
library(data.table)
sample <- setDT(sample)
sample[ , diff_year := year - shift(year), by = companyID]
sample <- setDF(sample)
sample
#> companyID year yearID diff_year
#> 1 1 2010 1 NA
#> 2 1 2011 2 1
#> 3 1 2012 3 1
#> 4 1 2013 4 1
#> 5 2 2010 1 NA
#> 6 2 2011 2 1
#> 7 2 2016 3 5
#> 8 2 2017 4 1
#> 9 2 2018 5 1
#> 10 3 2010 1 NA
#> 11 3 2011 2 1
#> 12 3 2014 3 3
#> 13 3 2017 4 3
#> 14 3 2018 5 1
# Created on 2021-03-13 by the reprex package (v1.0.0.9002)
Related to Calculate difference between values in consecutive rows by group
Regards,