How do you change observations iteratively in R?

You can create a sequence of date starting on the 1st of January, with 1 month intervals, and length as the number of observations per group.

df %>% 
   group_by(Student) %>% 
   mutate(Date = seq(as.Date(ISOdate(first(Date), 1, 1)), by = '1 month', length.out = n()))

   Student Date       Grade
   <chr>   <date>     <dbl>
 1 Walton  2018-01-01  0.77
 2 Walton  2018-02-01  0.77
 3 Walton  2018-03-01  0.77
 4 Walton  2018-04-01  0.77
 5 Walton  2018-05-01  0.77
 6 Walton  2018-06-01  0.77
 7 Walton  2018-07-01  0.77
 8 Walton  2018-08-01  0.77
 9 Walton  2018-09-01  0.77
10 Walton  2018-10-01  0.77
# ... with 14 more rows

If you can manually add the date, then use:

seq(as.Date("2018-01-01"), by = '1 month', length.out = n())

If you know that there are going to be twelve observations per group, use:

seq(as.Date("2018-01-01"), as.Date("2018-12-01"))

Using lubridate, another option is to use the %m+% operator:

library(lubridate)
df %>% 
   group_by(Student) %>% 
   mutate(Date = ymd(first(Date), truncated = 2) %m+% months(c(0:11)))

You can try to use data.table package :

library(data.table)
library(lubridate)
library(magrittr)
dt <- fread("
Student Date    Grade
Walton  2018    .77
Walton  2018    .77
Walton  2018    .77
Walton  2018    .77
Walton  2018    .77
Walton  2018    .77
Walton  2018    .77
Walton  2018    .77
Walton  2018    .77
Walton  2018    .77
Walton  2018    .77
Walton  2018    .77
Sam 2018    .86
Sam 2018    .86
Sam 2018    .86
Sam 2018    .86
Sam 2018    .86
Sam 2018    .86
Sam 2018    .86
Sam 2018    .86
Sam 2018    .86
Sam 2018    .86
Sam 2018    .86
Sam 2018    .86")

dt[,Month := 1:.N, by = Student] %>%
  .[, NewDate := make_date (Date, Month, 1)]

Here is the result :

> dt
    Student Date Grade Month    NewDate
 1:  Walton 2018  0.77     1 2018-01-01
 2:  Walton 2018  0.77     2 2018-02-01
 3:  Walton 2018  0.77     3 2018-03-01
 4:  Walton 2018  0.77     4 2018-04-01
 5:  Walton 2018  0.77     5 2018-05-01
 6:  Walton 2018  0.77     6 2018-06-01
 7:  Walton 2018  0.77     7 2018-07-01
 8:  Walton 2018  0.77     8 2018-08-01
 9:  Walton 2018  0.77     9 2018-09-01
10:  Walton 2018  0.77    10 2018-10-01
11:  Walton 2018  0.77    11 2018-11-01
12:  Walton 2018  0.77    12 2018-12-01
13:     Sam 2018  0.86     1 2018-01-01
14:     Sam 2018  0.86     2 2018-02-01
15:     Sam 2018  0.86     3 2018-03-01
16:     Sam 2018  0.86     4 2018-04-01
17:     Sam 2018  0.86     5 2018-05-01
18:     Sam 2018  0.86     6 2018-06-01
19:     Sam 2018  0.86     7 2018-07-01
20:     Sam 2018  0.86     8 2018-08-01
21:     Sam 2018  0.86     9 2018-09-01
22:     Sam 2018  0.86    10 2018-10-01
23:     Sam 2018  0.86    11 2018-11-01
24:     Sam 2018  0.86    12 2018-12-01
    Student Date Grade Month    NewDate

Here is another dplyr approach:

mutate a helper column x with 1 to 12,

paste it together and wrap it around as.Date

library(dplyr)

df %>% 
  mutate(x = rep(1:12, length.out = n()),
         Date = as.Date(paste(Date,x,"01",sep = "-")), .keep="unused")

Student       Date Grade
1   Walton 2018-01-01  0.77
2   Walton 2018-02-01  0.77
3   Walton 2018-03-01  0.77
4   Walton 2018-04-01  0.77
5   Walton 2018-05-01  0.77
6   Walton 2018-06-01  0.77
7   Walton 2018-07-01  0.77
8   Walton 2018-08-01  0.77
9   Walton 2018-09-01  0.77
10  Walton 2018-10-01  0.77
11  Walton 2018-11-01  0.77
12  Walton 2018-12-01  0.77
13     Sam 2018-01-01  0.86
14     Sam 2018-02-01  0.86
15     Sam 2018-03-01  0.86
16     Sam 2018-04-01  0.86
17     Sam 2018-05-01  0.86
18     Sam 2018-06-01  0.86
19     Sam 2018-07-01  0.86
20     Sam 2018-08-01  0.86
21     Sam 2018-09-01  0.86
22     Sam 2018-10-01  0.86
23     Sam 2018-11-01  0.86
24     Sam 2018-12-01  0.86