How to find a Sequence with in a column Using R-CodePudding

I am fairly new to R. I am trying to figure out a way to verify a sequence within a column. I tried using seq() but that's not really providing me much.

Here is a sample of the df

    gp<-data.frame(Id=c(1503960366,1503960366,1503960366,4319703577,4319703577,4319703577,5553957443,5553957443,5553957443),
  date=c("2016-04-27", "2016-04-12","2016-04-27", "2016-04-12", "2016-04-27","2016-04-27","2016-5-16","2016-4-16", "2016-5-16),
Cal=c(1347,1347,1348,1496,1497,1496,1688,1688,1688,2063,2063,2064))

The sequence is within column Cal. Each set of cal per Id has an increase of 1. What I want to do is verify or search for the sequence then create a new column that verifies the increase of 1 in True or false for that Id

##This is the printed-out version of the df.
        Id date         Cal
      <dbl> <chr>      <dbl>
1 1503960366 2016-04-27  1347
2 1503960366 2016-04-12  1347
3 1503960366 2016-04-27  1348
4 4319703577 2016-04-12  1496
5 4319703577 2016-04-27  1497
6 4319703577 2016-04-27  1496
7 5553957443 2016-5-16   1688
8 5553957443 2016-4-16   1688
9 5553957443 2016-5-16   1688

##This is the outcome I am looking for

         Id date         Cal  Verify
      <dbl> <chr>      <dbl>   <dbl>
1 1503960366 2016-04-27  1347   False
2 1503960366 2016-04-12  1347   False
3 1503960366 2016-04-27  1348   True
4 4319703577 2016-04-12  1496   False
5 4319703577 2016-04-27  1497   True
6 4319703577 2016-04-27  1496   False 
7 5553957443 2016-5-16   1688   False
8 5553957443 2016-4-16   1688   False
9 5553957443 2016-5-16   1688   False

Any help or direction in the right place will be greatly appreciated. Thanks in advance.

CodePudding user response：

Subtract the current Cal value with the previous one and check if the difference is equal to 1.

library(dplyr)

df %>%
  mutate(Verify = Cal - lag(Cal, default = 0) == 1)

#          Id       date  Cal Verify
#1 1503960366 2016-04-27 1347  FALSE
#2 1503960366 2016-04-12 1347  FALSE
#3 1503960366 2016-04-27 1348   TRUE
#4 4319703577 2016-04-12 1496  FALSE
#5 4319703577 2016-04-27 1497   TRUE
#6 4319703577 2016-04-27 1496  FALSE
#7 5553957443  2016-5-16 1688  FALSE
#8 5553957443  2016-4-16 1688  FALSE
#9 5553957443  2016-5-16 1688  FALSE

In base R -

df$Verify <- c(FALSE, df$Cal[-1] - df$Cal[-nrow(df)] == 1)

data

df <- structure(list(Id = c(1503960366, 1503960366, 1503960366, 4319703577, 
4319703577, 4319703577, 5553957443, 5553957443, 5553957443), 
    date = c("2016-04-27", "2016-04-12", "2016-04-27", "2016-04-12", 
    "2016-04-27", "2016-04-27", "2016-5-16", "2016-4-16", "2016-5-16"
    ), Cal = c(1347L, 1347L, 1348L, 1496L, 1497L, 1496L, 1688L, 
    1688L, 1688L)), class = "data.frame", row.names = c(NA, -9L))

CodePudding user response：

Using diff.

df <- transform(df, Verify=c(0, diff(Cal)) == 1)
df
#           Id       date  Cal Verify
# 1 1503960366 2016-04-27 1347  FALSE
# 2 1503960366 2016-04-12 1347  FALSE
# 3 1503960366 2016-04-27 1348   TRUE
# 4 4319703577 2016-04-12 1496  FALSE
# 5 4319703577 2016-04-27 1497   TRUE
# 6 4319703577 2016-04-27 1496  FALSE
# 7 5553957443  2016-5-16 1688  FALSE
# 8 5553957443  2016-4-16 1688  FALSE
# 9 5553957443  2016-5-16 1688  FALSE